Theofanis Karaletsos

53 papers A* 11A 1Journal 37Unranked 4
YearRankTypeTitle / Venue / Authors
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
Statistical and structural identifiability in representation learning.
CoRR
Walter Nelson, Marco Fumero, Theofanis Karaletsos, Francesco Locatello
2025 J jnl
How Well Do LLMs Understand Drug Mechanisms? A Knowledge + Reasoning Evaluation Dataset.
CoRR
Sunil Mohan, Theofanis Karaletsos
2025 — conf
How Well Does ChatGPT Understand Drug Mechanisms? A Knowledge + Reasoning Evaluation Dataset.
FLLM
Sunil Mohan, Theofanis Karaletsos
2025 J jnl
Learning Explicit Single-Cell Dynamics Using ODE Representations.
CoRR
Jan-Philipp von Bassewitz, Adeel Pervez, Marco Fumero, Matthew Robinson, Theofanis Karaletsos, Francesco Locatello
2025 J jnl
MorphGen: Controllable and Morphologically Plausible Generative Cell-Imaging.
CoRR
Berker Demirel, Marco Fumero, Theofanis Karaletsos, Francesco Locatello
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 J jnl
Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models.
CoRR
Giovanni Palla, Sudarshan Babu, Payam Dibaeinia, James D. Pearce, Donghui Li, Aly A. Khan, Theofanis Karaletsos, Jakub M. Tomczak
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
Adjusting Pretrained Backbones for Performativity.
CoRR
Berker Demirel, Lingjing Kong, Kun Zhang, Theofanis Karaletsos, Celestine Mendler-Dünner, Francesco Locatello
2024 A* conf
Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words.
ICLR
Yujia Bao, Srinivasan Sivanandan, Theofanis Karaletsos
2024 J jnl
Compositional Deep Probabilistic Models of DNA-Encoded Libraries.
J. Chem. Inf. Model.
Benson Chen, Mohammad M. Sultan, Theofanis Karaletsos
2024 J jnl
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities.
CoRR
Charlotte Bunne, Yusuf H. Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, Mohammed AlQuraishi, Patricia Brennan, Daniel B. Burkhardt, Andrea Califano, Jonah Cool, Abby F. Dernburg, Kirsty Ewing, Emily B. Fox, Matthias Haury, Amy E. Herr, Eric Horvitz, Patrick D. Hsu, Viren Jain, Gregory R. Johnson, Thomas Kalil, David R. Kelley, Shana O. Kelley, Anna Kreshuk, Tim Mitchison, Stephani Otte, Jay Shendure, Nicolas J. Sofroniew, Fabian J. Theis, Christina V. Theodoris, Srigokul Upadhyayula, Marc Valer, Bo Wang, Eric Xing, Serena Yeung-Levy, Marinka Zitnik, Theofanis Karaletsos, Aviv Regev, Emma Lundberg, Jure Leskovec, Stephen R. Quake
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
2023 J jnl
Channel Vision Transformers: An Image Is Worth C x 16 x 16 Words.
CoRR
Yujia Bao, Srinivasan Sivanandan, Theofanis Karaletsos
2023 J jnl
Contextual Vision Transformers for Robust Representation Learning.
CoRR
Yujia Bao, Theofanis Karaletsos
2023 J jnl
DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries.
J. Chem. Inf. Model.
Kirill Shmilovich, Benson Chen, Theofanis Karaletsos, Mohammad M. Sultan
2023 A* conf
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder.
NeurIPS
Michael Bereket, Theofanis Karaletsos
2023 J jnl
Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder.
CoRR
Michael Bereket, Theofanis Karaletsos
2022 J jnl
Black-box Coreset Variational Inference.
CoRR
Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos
2022 A* conf
Black-box coreset variational inference.
NeurIPS
Dionysis Manousakas, Hippolyt Ritter, Theofanis Karaletsos
2022 J jnl
DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries.
CoRR
Kirill Shmilovich, Benson Chen, Theofanis Karaletsos, Mohammad M. Sultan
2022 — conf
TyXe: Pyro-based Bayesian neural nets for Pytorch.
MLSys
Hippolyt Ritter, Theofanis Karaletsos
2021 J jnl
Localized Uncertainty Attacks.
CoRR
Ousmane Amadou Dia, Theofanis Karaletsos, Caner Hazirbas, Cristian Canton-Ferrer, Ilknur Kaynar Kabul, Erik Meijer
2021 J jnl
Stochastic Aggregation in Graph Neural Networks.
CoRR
Yuanqing Wang, Theofanis Karaletsos
2021 J jnl
TyXe: Pyro-based Bayesian neural nets for Pytorch.
CoRR
Hippolyt Ritter, Theofanis Karaletsos
2021 A* conf
Variational Auto-Regressive Gaussian Processes for Continual Learning.
ICML
Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui
2020 J jnl
Generalized Hidden Parameter MDPs Transferable Model-based RL in a Handful of Trials.
CoRR
Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos
2020 A* conf
Generalized Hidden Parameter MDPs: Transferable Model-Based RL in a Handful of Trials.
AAAI
Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos
2020 A* conf
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights.
NeurIPS
Theofanis Karaletsos, Thang D. Bui
2020 J jnl
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights.
CoRR
Theofanis Karaletsos, Thang D. Bui
2020 J jnl
Variational Auto-Regressive Gaussian Processes for Continual Learning.
CoRR
Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui
2019 J jnl
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference.
CoRR
Xinyu Hu, Paul A. Szerlip, Theofanis Karaletsos, Rohit Singh
2019 A conf
Pathwise Derivatives for Multivariate Distributions.
AISTATS
Martin Jankowiak, Theofanis Karaletsos
2019 J jnl
Pyro: Deep Universal Probabilistic Programming.
J. Mach. Learn. Res.
Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul A. Szerlip, Paul Horsfall, Noah D. Goodman
2018 J jnl
Efficient transfer learning and online adaptation with latent variable models for continuous control.
CoRR
Christian F. Perez, Felipe Petroski Such, Theofanis Karaletsos
2018 — conf
Likelihood-free inference with emulator networks.
AABI
Jan-Matthis Lueckmann, Giacomo Bassetto, Theofanis Karaletsos, Jakob H. Macke
2018 J jnl
Likelihood-free inference with emulator networks.
CoRR
Jan-Matthis Lueckmann, Giacomo Bassetto, Theofanis Karaletsos, Jakob H. Macke
2018 J jnl
Pathwise Derivatives for Multivariate Distributions.
CoRR
Martin Jankowiak, Theofanis Karaletsos
2018 J jnl
Probabilistic Meta-Representations Of Neural Networks.
CoRR
Theofanis Karaletsos, Peter Dayan, Zoubin Ghahramani
2018 J jnl
Pyro: Deep Universal Probabilistic Programming.
CoRR
Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul A. Szerlip, Paul Horsfall, Noah D. Goodman
2017 A* conf
Conditional Similarity Networks.
CVPR
Andreas Veit, Serge J. Belongie, Theofanis Karaletsos
2017 J jnl
RiboDiff: detecting changes of mRNA translation efficiency from ribosome footprints.
Bioinform.
Yi Zhong, Theofanis Karaletsos, Philipp Drewe, Vipin T. Sreedharan, David Kuo, Kamini Singh, Hans-Guido Wendel, Gunnar Rätsch
2016 A* conf
A Generative Model of Words and Relationships from Multiple Sources.
AAAI
Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch
2016 J jnl
Adversarial Message Passing For Graphical Models.
CoRR
Theofanis Karaletsos
2016 J jnl
Disentangling Nonlinear Perceptual Embeddings With Multi-Query Triplet Networks.
CoRR
Andreas Veit, Serge J. Belongie, Theofanis Karaletsos
2016 J jnl
Knowledge Transfer with Medical Language Embeddings.
CoRR
Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch
2016 A* conf
When crowds hold privileges: Bayesian unsupervised representation learning with oracle constraints.
ICLR (Poster)
Theofanis Karaletsos, Serge J. Belongie, Gunnar Rätsch
2015 J jnl
A Generative Model of Words and Relationships from Multiple Sources.
CoRR
Stephanie L. Hyland, Theofanis Karaletsos, Gunnar Rätsch
2013 — conf
An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes.
ICDM Workshops
Katherine Redfield Chan, Xinghua Lou, Theofanis Karaletsos, Christopher Crosbie, Stuart M. Gardos, David Artz, Gunnar Rätsch
2012 J jnl
ShapePheno: unsupervised extraction of shape phenotypes from biological image collections.
Bioinform.
Theofanis Karaletsos, Oliver Stegle, Christine Dreyer, John M. Winn, Karsten M. Borgwardt