Stephan Mandt - RankMe

181 papers A* 44A 14B 1Journal 111Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Advances in Diffusion-Based Generative Compression. CoRR Yibo Yang, Stephan Mandt
2026	J	`jnl`	Calibrated Test-Time Guidance for Bayesian Inference. CoRR Daniel Geyfman, Felix Draxler, Jan Groeneveld, Hyunsoo Lee, Theofanis Karaletsos, Stephan Mandt
2026	J	`jnl`	Structure is Supervision: Multiview Masked Autoencoders for Radiology. Trans. Mach. Learn. Res. Sonia Laguna, Andrea Agostini, Alain Ryser, Samuel Ruipérez-Campillo, Irene Cannistraci, Moritz Vandenhirtz, Stephan Mandt, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E. Vogt
2025	J	`jnl`	A machine-learned expression for the excess Gibbs energy. CoRR Marco Hoffmann, Thomas Specht, Quirin Göttl, Jakob Burger, Stephan Mandt, Hans Hasse, Fabian Jirasek
2025	A*	`conf`	AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data. ICLR Tuan Truong, Rithwik Sudharsan, Yibo Yang, Peter Xiangyuan Ma, Ruihan Yang, Stephan Mandt, Joshua S. Bloom
2025	J	`jnl`	AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data. CoRR Tuan Truong, Rithwik Sudharsan, Yibo Yang, Peter Xiangyuan Ma, Ruihan Yang, Stephan Mandt, Joshua S. Bloom
2025	J	`jnl`	ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation. J. Mach. Learn. Res. Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Helge Heuer, Benjamin R. Hillman, Andrea M. Jenney, Nana Liu, Alistair White, Tian Zheng, Zhiming Kuang, Fiaz Ahmed, Elizabeth A. Barnes, Noah D. Brenowitz, Christopher S. Bretherton, Veronika Eyring, Savannah L. Ferretti, Nicholas J. Lutsko, Pierre Gentine, Stephan Mandt, J. David Neelin, Rose Yu, Laure Zanna, Nathan M. Urban, Janni Yuval, Ryan Abernathey, Pierre Baldi, Wayne Chuang, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Po-Lun Ma, Sara Shamekh, Guang Zhang, Michael S. Pritchard
2025	J	`jnl`	Control-Augmented Autoregressive Diffusion for Data Assimilation. CoRR Prakhar Srivastava, Farrin Marouf Sofian, Francesco Immorlano, Kushagra Pandey, Stephan Mandt
2025	J	`jnl`	DiffStyleTS: Diffusion Model for Style Transfer in Time Series. CoRR Mayank Nagda, Phil Ostheimer, Justus Arweiler, Indra Jungjohann, Jennifer Werner, Dennis Wagner, Aparna Muraleedharan, Pouya Jafari, Jochen Schmid, Fabian Jirasek, Jakob Burger, Michael Bortz, Hans Hasse, Stephan Mandt, Marius Kloft, Sophie Fellenz
2025	J	`jnl`	Diffusion-Guided Gaussian Splatting for Large-Scale Unconstrained 3D Reconstruction and Novel View Synthesis. CoRR Niluthpol Chowdhury Mithun, Tuan Pham, Qiao Wang, Ben Southall, Kshitij Minhas, Bogdan Matei, Stephan Mandt, Supun Samarasekera, Rakesh Kumar
2025	J	`jnl`	Formally Exploring Time-Series Anomaly Detection Evaluation Metrics. CoRR Dennis Wagner, Arjun Nair, Billy Joe Franks, Justus Arweiler, Aparna Muraleedharan, Indra Jungjohann, Fabian Hartung, Mayank C. Ahuja, Andriy Balinskyy, Saurabh Varshneya, Nabeel Hussain Syed, Mayank Nagda, Philipp Liznerski, Steffen Reithermann, Maja Rudolph, Sebastian J. Vollmer, Ralf Schulz, Torsten Katz, Stephan Mandt, Michael Bortz, Heike Leitte, Daniel Neider, Jakob Burger, Fabian Jirasek, Hans Hasse, Sophie Fellenz, Marius Kloft
2025	A	`conf`	Generative Uncertainty in Diffusion Models. UAI Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric T. Nalisnick, Stephan Mandt
2025	J	`jnl`	Generative Uncertainty in Diffusion Models. CoRR Metod Jazbec, Eliot Wong-Toi, Guoxuan Xia, Dan Zhang, Eric T. Nalisnick, Stephan Mandt
2025	—	`conf`	GeoDiff: Geometry-Guided Diffusion for Metric Depth Estimation. ICCVW Tuan Pham, Thanh-Tung Le, Xiaohui Xie, Stephan Mandt
2025	J	`jnl`	GeoDiff: Geometry-Guided Diffusion for Metric Depth Estimation. CoRR Tuan Pham, Thanh-Tung Le, Xiaohui Xie, Stephan Mandt
2025	A*	`conf`	Heavy-Tailed Diffusion Models. ICLR Kushagra Pandey, Jaideep Pathak, Yilun Xu, Stephan Mandt, Michael S. Pritchard, Arash Vahdat, Morteza Mardani
2025	A	`ed.`	International Conference on Artificial Intelligence and Statistics, AISTATS 2025, Mai Khao, Thailand, 3-5 May 2025. AISTATS Yingzhen Li, Stephan Mandt, Shipra Agrawal, Mohammad Emtiyaz Khan
2025	J	`jnl`	JANET: Joint Adaptive predictioN-region Estimation for Time-series. Mach. Learn. Eshant English, Eliot Wong-Toi, Matteo Fontana, Stephan Mandt, Padhraic Smyth, Christoph Lippert
2025	J	`jnl`	On the Challenges and Opportunities in Generative AI. Trans. Mach. Learn. Res. Laura Manduchi, Clara Meister, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin
2025	J	`jnl`	On the Effect of Regularization on Nonparametric Mean-Variance Regression. CoRR Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
2025	A*	`conf`	One Diffusion to Generate Them All. CVPR Duong H. Le, Tuan Pham, Sangho Lee, Christopher Clark, Aniruddha Kembhavi, Stephan Mandt, Ranjay Krishna, Jiasen Lu
2025	J	`jnl`	Parallel Token Prediction for Language Models. CoRR Felix Draxler, Justus C. Will, Farrin Marouf Sofian, Theofanis Karaletsos, Sameer Singh, Stephan Mandt
2025	A*	`conf`	Progressive Compression with Universally Quantized Diffusion Models. ICLR Yibo Yang, Justus C. Will, Stephan Mandt
2025	J	`jnl`	Self-Supervised Anomaly Detection With Neural Transformations. IEEE Trans. Pattern Anal. Mach. Intell. Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2025	J	`jnl`	Structure is Supervision: Multiview Masked Autoencoders for Radiology. CoRR Sonia Laguna, Andrea Agostini, Alain Ryser, Samuel Ruipérez-Campillo, Irene Cannistraci, Moritz Vandenhirtz, Stephan Mandt, Nicolas Deperrois, Farhad Nooralahzadeh, Michael Krauthammer, Thomas M. Sutter, Julia E. Vogt
2025	J	`jnl`	UMAMI: Unifying Masked Autoregressive Models and Deterministic Rendering for View Synthesis. CoRR Thanh-Tung Le, Tuan Pham, Tung Nguyen, Deying Kong, Xiaohui Xie, Stephan Mandt
2025	A*	`conf`	Variational Control for Guidance in Diffusion Models. ICML Kushagra Pandey, Farrin Marouf Sofian, Felix Draxler, Theofanis Karaletsos, Stephan Mandt
2025	J	`jnl`	Variational Control for Guidance in Diffusion Models. CoRR Kushagra Pandey, Farrin Marouf Sofian, Felix Draxler, Theofanis Karaletsos, Stephan Mandt
2024	J	`jnl`	Advancing Thermodynamic Group-Contribution Methods by Machine Learning: UNIFAC 2.0. CoRR Nicolas Hayer, Thorsten Wendel, Stephan Mandt, Hans Hasse, Fabian Jirasek
2024	J	`jnl`	Anomaly Detection of Tabular Data Using LLMs. CoRR Aodong Li, Yunhan Zhao, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2024	A	`conf`	Early-Exit Neural Networks with Nested Prediction Sets. UAI Metod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric T. Nalisnick
2024	A*	`conf`	Efficient Integrators for Diffusion Generative Models. ICLR Kushagra Pandey, Maja Rudolph, Stephan Mandt
2024	J	`jnl`	Fast Samplers for Inverse Problems in Iterative Refinement Models. CoRR Kushagra Pandey, Ruihan Yang, Stephan Mandt
2024	A*	`conf`	Fast samplers for Inverse Problems in Iterative Refinement models. NeurIPS Kushagra Pandey, Ruihan Yang, Stephan Mandt
2024	J	`jnl`	HANNA: Hard-constraint Neural Network for Consistent Activity Coefficient Prediction. CoRR Thomas Specht, Mayank Nagda, Sophie Fellenz, Stephan Mandt, Hans Hasse, Fabian Jirasek
2024	J	`jnl`	Heavy-Tailed Diffusion Models. CoRR Kushagra Pandey, Jaideep Pathak, Yilun Xu, Stephan Mandt, Michael S. Pritchard, Arash Vahdat, Morteza Mardani
2024	A	`ed.`	International Conference on Artificial Intelligence and Statistics, 2-4 May 2024, Palau de Congressos, Valencia, Spain. AISTATS Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li
2024	J	`jnl`	JANET: Joint Adaptive predictioN-region Estimation for Time-series. CoRR Eshant English, Eliot Wong-Toi, Matteo Fontana, Stephan Mandt, Padhraic Smyth, Christoph Lippert
2024	A*	`conf`	Neural NeRF Compression. ICML Tuan Pham, Stephan Mandt
2024	J	`jnl`	Neural NeRF Compression. CoRR Tuan Pham, Stephan Mandt
2024	J	`jnl`	On the Challenges and Opportunities in Generative AI. CoRR Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric T. Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E. Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin
2024	J	`jnl`	One Diffusion to Generate Them All. CoRR Duong H. Le, Tuan Pham, Sangho Lee, Christopher Clark, Aniruddha Kembhavi, Stephan Mandt, Ranjay Krishna, Jiasen Lu
2024	J	`jnl`	Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI. CoRR Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. ICML Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael A. Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang
2024	A*	`conf`	Precipitation Downscaling with Spatiotemporal Video Diffusion. NeurIPS Prakhar Srivastava, Ruihan Yang, Gavin Kerrigan, Gideon Dresdner, Jeremy McGibbon, Christopher S. Bretherton, Stephan Mandt
2024	J	`jnl`	Preserving Identity with Variational Score for General-purpose 3D Editing. CoRR Duong H. Le, Tuan Pham, Aniruddha Kembhavi, Stephan Mandt, Wei-Chiu Ma, Jiasen Lu
2024	J	`jnl`	Progressive Compression with Universally Quantized Diffusion Models. CoRR Yibo Yang, Justus C. Will, Stephan Mandt
2024	J	`jnl`	Towards Fast Stochastic Sampling in Diffusion Generative Models. CoRR Kushagra Pandey, Maja Rudolph, Stephan Mandt
2024	A	`conf`	Understanding Pathologies of Deep Heteroskedastic Regression. UAI Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
2024	A*	`conf`	Unity by Diversity: Improved Representation Learning for Multimodal VAEs. NeurIPS Thomas M. Sutter, Yang Meng, Andrea Agostini, Daphné Chopard, Norbert Fortin, Julia E. Vogt, Babak Shahbaba, Stephan Mandt
2024	J	`jnl`	Unity by Diversity: Improved Representation Learning in Multimodal VAEs. CoRR Thomas M. Sutter, Yang Meng, Norbert Fortin, Julia E. Vogt, Stephan Mandt
2024	J	`jnl`	Weakly-Supervised Multimodal Learning on MIMIC-CXR. CoRR Andrea Agostini, Daphné Chopard, Yang Meng, Norbert Fortin, Babak Shahbaba, Stephan Mandt, Thomas M. Sutter, Julia E. Vogt
2023	A*	`conf`	A Complete Recipe for Diffusion Generative Models. ICCV Kushagra Pandey, Stephan Mandt
2023	J	`jnl`	An Introduction to Neural Data Compression. Found. Trends Comput. Graph. Vis. Yibo Yang, Stephan Mandt, Lucas Theis
2023	J	`jnl`	Anytime-Valid Confidence Sequences for Consistent Uncertainty Estimation in Early-Exit Neural Networks. CoRR Metod Jazbec, Patrick Forré, Stephan Mandt, Dan Zhang, Eric T. Nalisnick
2023	J	`jnl`	Asymmetrically-powered Neural Image Compression with Shallow Decoders. CoRR Yibo Yang, Stephan Mandt
2023	J	`jnl`	Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072). Dagstuhl Reports Vincent Fortuin, Yingzhen Li, Kevin Murphy, Stephan Mandt, Laura Manduchi
2023	A*	`conf`	ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard
2023	J	`jnl`	ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.
2023	A*	`conf`	Computationally-Efficient Neural Image Compression with Shallow Decoders. ICCV Yibo Yang, Stephan Mandt
2023	J	`jnl`	Deep Anomaly Detection on Tennessee Eastman Process Data. CoRR Fabian Hartung, Billy Joe Franks, Tobias Michels, Dennis Wagner, Philipp Liznerski, Steffen Reithermann, Sophie Fellenz, Fabian Jirasek, Maja Rudolph, Daniel Neider, Heike Leitte, Chen Song, Benjamin Klöpper, Stephan Mandt, Michael Bortz, Jakob Burger, Hans Hasse, Marius Kloft
2023	A*	`conf`	Deep Anomaly Detection under Labeling Budget Constraints. ICML Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph
2023	J	`jnl`	Deep Anomaly Detection under Labeling Budget Constraints. CoRR Aodong Li, Chen Qiu, Padhraic Smyth, Marius Kloft, Stephan Mandt, Maja Rudolph
2023	J	`jnl`	Diffusion Probabilistic Modeling for Video Generation. Entropy Ruihan Yang, Prakhar Srivastava, Stephan Mandt
2023	J	`jnl`	Efficient Integrators for Diffusion Generative Models. CoRR Kushagra Pandey, Maja Rudolph, Stephan Mandt
2023	A*	`conf`	Estimating the Rate-Distortion Function by Wasserstein Gradient Descent. NeurIPS Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt
2023	J	`jnl`	Estimating the Rate-Distortion Function by Wasserstein Gradient Descent. CoRR Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt
2023	A*	`conf`	Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes. ICML Ba-Hien Tran, Babak Shahbaba, Stephan Mandt, Maurizio Filippone
2023	J	`jnl`	Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes. CoRR Ba-Hien Tran, Babak Shahbaba, Stephan Mandt, Maurizio Filippone
2023	J	`jnl`	Generative Diffusions in Augmented Spaces: A Complete Recipe. CoRR Kushagra Pandey, Stephan Mandt
2023	A	`conf`	Inference for mark-censored temporal point processes. UAI Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2023	J	`jnl`	Insights From Generative Modeling for Neural Video Compression. IEEE Trans. Pattern Anal. Mach. Intell. Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
2023	A*	`conf`	Lossy Image Compression with Conditional Diffusion Models. NeurIPS Ruihan Yang, Stephan Mandt
2023	J	`jnl`	Probabilistic Precipitation Downscaling with Optical Flow-Guided Diffusion. CoRR Prakhar Srivastava, Ruihan Yang, Gavin Kerrigan, Gideon Dresdner, Jeremy McGibbon, Christopher S. Bretherton, Stephan Mandt
2023	A	`conf`	Probabilistic Querying of Continuous-Time Event Sequences. AISTATS Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2023	J	`jnl`	SC2 Benchmark: Supervised Compression for Split Computing. Trans. Mach. Learn. Res. Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2023	J	`jnl`	Understanding Pathologies of Deep Heteroskedastic Regression. CoRR Eliot Wong-Toi, Alex Boyd, Vincent Fortuin, Stephan Mandt
2023	J	`jnl`	Understanding and Visualizing Droplet Distributions in Simulations of Shallow Clouds. CoRR Justus C. Will, Andrea M. Jenney, Kara D. Lamb, Michael S. Pritchard, Colleen Kaul, Po-Lun Ma, Kyle Pressel, Jacob Shpund, Marcus van Lier-Walqui, Stephan Mandt
2023	A*	`conf`	Zero-Shot Anomaly Detection via Batch Normalization. NeurIPS Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2023	J	`jnl`	Zero-Shot Anomaly Detection without Foundation Models. CoRR Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	An Introduction to Neural Data Compression. CoRR Yibo Yang, Stephan Mandt, Lucas Theis
2022	J	`jnl`	Detecting Anomalies within Time Series using Local Neural Transformations. CoRR Tim Schneider, Chen Qiu, Marius Kloft, Decky Aspandi-Latif, Steffen Staab, Stephan Mandt, Maja Rudolph
2022	J	`jnl`	Diffusion Probabilistic Modeling for Video Generation. CoRR Ruihan Yang, Prakhar Srivastava, Stephan Mandt
2022	J	`jnl`	Improving sequential latent variable models with autoregressive flows. Mach. Learn. Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt
2022	A*	`conf`	Latent Outlier Exposure for Anomaly Detection with Contaminated Data. ICML Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	Latent Outlier Exposure for Anomaly Detection with Contaminated Data. CoRR Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt
2022	A*	`conf`	Lossless Compression with Probabilistic Circuits. ICLR Anji Liu, Stephan Mandt, Guy Van den Broeck
2022	J	`jnl`	Lossy Image Compression with Conditional Diffusion Models. CoRR Ruihan Yang, Stephan Mandt
2022	A*	`conf`	Predictive Querying for Autoregressive Neural Sequence Models. NeurIPS Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth
2022	J	`jnl`	Predictive Querying for Autoregressive Neural Sequence Models. CoRR Alex Boyd, Samuel Showalter, Stephan Mandt, Padhraic Smyth
2022	J	`jnl`	Probabilistic Querying of Continuous-Time Event Sequences. CoRR Alex Boyd, Yuxin Chang, Stephan Mandt, Padhraic Smyth
2022	A*	`conf`	Raising the Bar in Graph-level Anomaly Detection. IJCAI Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2022	J	`jnl`	Raising the Bar in Graph-level Anomaly Detection. CoRR Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2022	J	`jnl`	SC2: Supervised Compression for Split Computing. CoRR Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2022	A*	`conf`	Structured Stochastic Gradient MCMC. ICML Antonios Alexos, Alex J. Boyd, Stephan Mandt
2022	A	`conf`	Supervised Compression for Resource-Constrained Edge Computing Systems. WACV Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2022	A*	`conf`	Towards Empirical Sandwich Bounds on the Rate-Distortion Function. ICLR Yibo Yang, Stephan Mandt
2021	J	`jnl`	Analyzing High-Resolution Clouds and Convection using Multi-Channel VAEs. CoRR Harshini Mangipudi, Griffin Mooers, Mike Pritchard, Tom Beucler, Stephan Mandt
2021	A*	`conf`	Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning. NeurIPS Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt
2021	A*	`conf`	Hierarchical Autoregressive Modeling for Neural Video Compression. ICLR Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
2021	J	`jnl`	History Marginalization Improves Forecasting in Variational Recurrent Neural Networks. Entropy Chen Qiu, Stephan Mandt, Maja Rudolph
2021	J	`jnl`	Insights from Generative Modeling for Neural Video Compression. CoRR Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
2021	J	`jnl`	Lossless Compression with Probabilistic Circuits. CoRR Anji Liu, Stephan Mandt, Guy Van den Broeck
2021	A*	`conf`	Neural Transformation Learning for Deep Anomaly Detection Beyond Images. ICML Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph
2021	J	`jnl`	Neural Transformation Learning for Deep Anomaly Detection Beyond Images. CoRR Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph
2021	A	`conf`	Scalable Gaussian Process Variational Autoencoders. AISTATS Metod Jazbec, Matthew Ashman, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch
2021	J	`jnl`	Structured Stochastic Gradient MCMC. CoRR Antonios Alexos, Alex Boyd, Stephan Mandt
2021	J	`jnl`	Supervised Compression for Resource-constrained Edge Computing Systems. CoRR Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt
2021	J	`jnl`	Towards Empirical Sandwich Bounds on the Rate-Distortion Function. CoRR Yibo Yang, Stephan Mandt
2020	A*	`conf`	Extreme Classification via Adversarial Softmax Approximation. ICLR Robert Bamler, Stephan Mandt
2020	J	`jnl`	Extreme Classification via Adversarial Softmax Approximation. CoRR Robert Bamler, Stephan Mandt
2020	A	`conf`	GP-VAE: Deep Probabilistic Time Series Imputation. AISTATS Vincent Fortuin, Dmitry Baranchuk, Gunnar Rätsch, Stephan Mandt
2020	J	`jnl`	Generative Modeling for Atmospheric Convection. CoRR Griffin Mooers, Jens Tuyls, Stephan Mandt, Michael S. Pritchard, Tom Beucler
2020	—	`conf`	Generative Modeling of Atmospheric Convection. CI Griffin Mooers, Jens Tuyls, Stephan Mandt, Mike Pritchard, Tom G. Beucler
2020	J	`jnl`	Hierarchical Autoregressive Modeling for Neural Video Compression. CoRR Ruihan Yang, Yibo Yang, Joseph Marino, Stephan Mandt
2020	A*	`conf`	How Good is the Bayes Posterior in Deep Neural Networks Really? ICML Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
2020	A*	`conf`	Improving Inference for Neural Image Compression. NeurIPS Yibo Yang, Robert Bamler, Stephan Mandt
2020	J	`jnl`	Improving Inference for Neural Image Compression. CoRR Yibo Yang, Robert Bamler, Stephan Mandt
2020	J	`jnl`	Improving Sequential Latent Variable Models with Autoregressive Flows. CoRR Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt
2020	J	`jnl`	Scalable Gaussian Process Variational Autoencoders. CoRR Metod Jazbec, Vincent Fortuin, Michael Pearce, Stephan Mandt, Gunnar Rätsch
2020	A*	`conf`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	J	`jnl`	The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
2020	A*	`conf`	User-Dependent Neural Sequence Models for Continuous-Time Event Data. NeurIPS Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
2020	J	`jnl`	User-Dependent Neural Sequence Models for Continuous-Time Event Data. CoRR Alex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth
2020	J	`jnl`	Variable-Bitrate Neural Compression via Bayesian Arithmetic Coding. CoRR Yibo Yang, Robert Bamler, Stephan Mandt
2020	A*	`conf`	Variational Bayesian Quantization. ICML Yibo Yang, Robert Bamler, Stephan Mandt
2020	J	`jnl`	Variational Beam Search for Online Learning with Distribution Shifts. CoRR Aodong Li, Alex Boyd, Padhraic Smyth, Stephan Mandt
2020	J	`jnl`	Variational Dynamic Mixtures. CoRR Chen Qiu, Stephan Mandt, Maja Rudolph
2019	J	`jnl`	A Quantum Field Theory of Representation Learning. CoRR Robert Bamler, Stephan Mandt
2019	A*	`conf`	Active Mini-Batch Sampling Using Repulsive Point Processes. AAAI Cheng Zhang, Cengiz Öztireli, Stephan Mandt, Giampiero Salvi
2019	J	`jnl`	Advances in Variational Inference. IEEE Trans. Pattern Anal. Mach. Intell. Cheng Zhang, Judith Bütepage, Hedvig Kjellström, Stephan Mandt
2019	A	`conf`	Augmenting and Tuning Knowledge Graph Embeddings. UAI Robert Bamler, Farnood Salehi, Stephan Mandt
2019	J	`jnl`	Augmenting and Tuning Knowledge Graph Embeddings. CoRR Robert Bamler, Farnood Salehi, Stephan Mandt
2019	—	`conf`	Autoregressive Text Generation Beyond Feedback Loops. EMNLP/IJCNLP (1) Florian Schmidt, Stephan Mandt, Thomas Hofmann
2019	J	`jnl`	Autoregressive Text Generation Beyond Feedback Loops. CoRR Florian Schmidt, Stephan Mandt, Thomas Hofmann
2019	A*	`conf`	Deep Generative Video Compression. NeurIPS Salvator Lombardo, Jun Han, Christopher Schroers, Stephan Mandt
2019	—	`conf`	Improving Sequential Latent Variable Models with Autoregressive Flows. AABI Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt
2019	A*	`conf`	Mobile Robotic Painting of Texture. ICRA Majed El Helou, Stephan Mandt, Andreas Krause, Paul A. Beardsley
2019	J	`jnl`	Multivariate Time Series Imputation with Variational Autoencoders. CoRR Vincent Fortuin, Gunnar Rätsch, Stephan Mandt
2019	J	`jnl`	Tightening Bounds for Variational Inference by Revisiting Perturbation Theory. CoRR Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
2018	J	`jnl`	A Deep Generative Model for Disentangled Representations of Sequential Data. CoRR Yingzhen Li, Stephan Mandt
2018	J	`jnl`	Active Mini-Batch Sampling using Repulsive Point Processes. CoRR Cheng Zhang, Cengiz Öztireli, Stephan Mandt, Giampiero Salvi
2018	B	`conf`	Continuous Word Embedding Fusion via Spectral Decomposition. CoNLL Tianfan Fu, Cheng Zhang, Stephan Mandt
2018	J	`jnl`	Deep Probabilistic Video Compression. CoRR Jun Han, Salvator Lombardo, Christopher Schroers, Stephan Mandt
2018	A*	`conf`	Disentangled Sequential Autoencoder. ICML Yingzhen Li, Stephan Mandt
2018	—	`conf`	Image Anomaly Detection with Generative Adversarial Networks. ECML/PKDD (1) Lucas Deecke, Robert A. Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft
2018	A*	`conf`	Improving Optimization in Models With Continuous Symmetry Breaking. ICML Robert Bamler, Stephan Mandt
2018	J	`jnl`	Improving Optimization in Models With Continuous Symmetry Breaking. CoRR Robert Bamler, Stephan Mandt
2018	A*	`conf`	Iterative Amortized Inference. ICML Joseph Marino, Yisong Yue, Stephan Mandt
2018	J	`jnl`	Iterative Amortized Inference. CoRR Joseph Marino, Yisong Yue, Stephan Mandt
2018	—	`conf`	Learning to Infer. ICLR (Workshop) Joseph Marino, Yisong Yue, Stephan Mandt
2018	A*	`conf`	Quasi-Monte Carlo Variational Inference. ICML Alexander Buchholz, Florian Wenzel, Stephan Mandt
2018	J	`jnl`	Quasi-Monte Carlo Variational Inference. CoRR Alexander Buchholz, Florian Wenzel, Stephan Mandt
2018	A	`conf`	Scalable Generalized Dynamic Topic Models. AISTATS Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
2018	J	`jnl`	Scalable Generalized Dynamic Topic Models. CoRR Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt
2017	J	`jnl`	Advances in Variational Inference. CoRR Cheng Zhang, Judith Bütepage, Hedvig Kjellström, Stephan Mandt
2017	A	`conf`	Balanced Mini-batch Sampling for SGD Using Determinantal Point Processes. UAI Cheng Zhang, Hedvig Kjellström, Stephan Mandt
2017	J	`jnl`	Bayesian Paragraph Vectors. CoRR Geng Ji, Robert Bamler, Erik B. Sudderth, Stephan Mandt
2017	J	`jnl`	Dynamic Word Embeddings via Skip-Gram Filtering. CoRR Robert Bamler, Stephan Mandt
2017	A*	`conf`	Dynamic Word Embeddings. ICML Robert Bamler, Stephan Mandt
2017	A*	`conf`	Factorized Variational Autoencoders for Modeling Audience Reactions to Movies. CVPR Zhiwei Deng, Rajitha Navarathna, Peter Carr, Stephan Mandt, Yisong Yue, Iain A. Matthews, Greg Mori
2017	—	`conf`	Perturbative Black Box Variational Inference. NIPS Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
2017	J	`jnl`	Perturbative Black Box Variational Inference. CoRR Robert Bamler, Cheng Zhang, Manfred Opper, Stephan Mandt
2017	J	`jnl`	Sparse probit linear mixed model. Mach. Learn. Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
2017	J	`jnl`	Stochastic Gradient Descent as Approximate Bayesian Inference. CoRR Stephan Mandt, Matthew D. Hoffman, David M. Blei
2017	J	`jnl`	Stochastic Gradient Descent as Approximate Bayesian Inference. J. Mach. Learn. Res. Stephan Mandt, Matthew D. Hoffman, David M. Blei
2017	J	`jnl`	Stochastic Learning on Imbalanced Data: Determinantal Point Processes for Mini-batch Diversification. CoRR Cheng Zhang, Hedvig Kjellström, Stephan Mandt
2017	J	`jnl`	Structured Black Box Variational Inference for Latent Time Series Models. CoRR Robert Bamler, Stephan Mandt
2016	A*	`conf`	A Variational Analysis of Stochastic Gradient Algorithms. ICML Stephan Mandt, Matthew D. Hoffman, David M. Blei
2016	J	`jnl`	A Variational Analysis of Stochastic Gradient Algorithms. CoRR Stephan Mandt, Matthew D. Hoffman, David M. Blei
2016	—	`conf`	Exponential Family Embeddings. NIPS Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei
2016	J	`jnl`	Exponential Family Embeddings. CoRR Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei
2016	—	`conf`	Huber-Norm Regularization for Linear Prediction Models. ECML/PKDD (1) Oleksandr Zadorozhnyi, Gunthard Benecke, Stephan Mandt, Tobias Scheffer, Marius Kloft
2016	—	`conf`	Separating Sparse Signals from Correlated Noise in Binary Classification. CFA@UAI Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft
2016	A	`conf`	Variational Tempering. AISTATS Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, David M. Blei
2015	J	`jnl`	Sparse Estimation in a Correlated Probit Model. CoRR Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft
2014	J	`jnl`	Deterministic Annealing for Stochastic Variational Inference. CoRR Farhan Abrol, Stephan Mandt, Rajesh Ranganath, David M. Blei
2014	—	`conf`	Smoothed Gradients for Stochastic Variational Inference. NIPS Stephan Mandt, David M. Blei
2014	J	`jnl`	Smoothed Gradients for Stochastic Variational Inference. CoRR Stephan Mandt, David M. Blei