Jonas Mueller - RankMe

64 papers A* 14A 2Journal 39Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Automated Data Curation for Robust Language Model Fine-Tuning. CoRR Jiuhai Chen, Jonas Mueller
2024	J	`jnl`	Detecting Errors in a Numerical Response via any Regression Model. J. Data-centric Mach. Learn. Res. Hang Zhou, Jonas Mueller, Mayank Kumar, Jane-Ling Wang, Jing Lei
2024	J	`jnl`	Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models. Trans. Mach. Learn. Res. Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
2024	—	`conf`	Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness. ACL (1) Jiuhai Chen, Jonas Mueller
2024	A*	`conf`	Time-Varying Propensity Score to Bridge the Gap between the Past and Present. ICLR Rasool Fakoor, Jonas Mueller, Zachary Chase Lipton, Pratik Chaudhari, Alex Smola
2023	J	`jnl`	ActiveLab: Active Learning with Re-Labeling by Multiple Annotators. CoRR Hui Wen Goh, Jonas Mueller
2023	J	`jnl`	Detecting Dataset Drift and Non-IID Sampling via k-Nearest Neighbors. CoRR Jesse Cummings, Elías Snorrason, Jonas Mueller
2023	J	`jnl`	Detecting Errors in Numerical Data via any Regression Model. CoRR Hang Zhou, Jonas Mueller, Mayank Kumar, Jane-Ling Wang, Jing Lei
2023	J	`jnl`	Estimating label quality and errors in semantic segmentation data via any model. CoRR Vedang Lad, Jonas Mueller
2023	J	`jnl`	Flexible Model Aggregation for Quantile Regression. J. Mach. Learn. Res. Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani
2023	J	`jnl`	ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data. CoRR Ulyana Tkachenko, Aditya Thyagarajan, Jonas Mueller
2023	J	`jnl`	Quantifying Uncertainty in Answers from any Language Model via Intrinsic and Extrinsic Confidence Assessment. CoRR Jiuhai Chen, Jonas Mueller
2023	—	`conf`	Task-Agnostic Continual Reinforcement Learning: Gaining Insights and Overcoming Challenges. CoLLAs Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor
2022	J	`jnl`	A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features. CoRR Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
2022	J	`jnl`	Back to the Basics: Revisiting Out-of-Distribution Detection Baselines. CoRR Johnson Kuan, Jonas Mueller
2022	J	`jnl`	Data drift correction via time-varying importance weight estimator. CoRR Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola
2022	J	`jnl`	DataPerf: Benchmarks for Data-Centric AI Development. CoRR Mark Mazumder, Colby R. Banbury, Xiaozhe Yao, Bojan Karlas, William Gaviria Rojas, Sudnya Frederick Diamos, Greg Diamos, Lynn He, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Juan Ciro, Lora Aroyo, Bilge Acun, Sabri Eyuboglu, Amirata Ghorbani, Emmett D. Goodman, Tariq Kane, Christine R. Kirkpatrick, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen K. Paritosh, Ce Zhang, James Zou, Carole-Jean Wu, Cody Coleman, Andrew Y. Ng, Peter Mattson, Vijay Janapa Reddi
2022	J	`jnl`	Detecting Label Errors in Token Classification Data. CoRR Wei-Chen Wang, Jonas Mueller
2022	A*	`conf`	Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. ICLR Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
2022	J	`jnl`	Identifying Incorrect Annotations in Multi-Label Classification Data. CoRR Aditya Thyagarajan, Elías Snorrason, Curtis G. Northcutt, Jonas Mueller
2022	—	`conf`	ResNeSt: Split-Attention Networks. CVPR Workshops Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Haibin Lin, Zhi Zhang, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
2022	J	`jnl`	Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline. CoRR Massimo Caccia, Jonas Mueller, Taesup Kim, Laurent Charlin, Rasool Fakoor
2022	J	`jnl`	Utilizing supervised models to infer consensus labels and their quality from data with multiple annotators. CoRR Hui Wen Goh, Ulyana Tkachenko, Jonas Mueller
2021	—	`conf`	Benchmarking Multimodal AutoML for Tabular Data with Text Fields. NeurIPS Datasets and Benchmarks Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
2021	J	`jnl`	Benchmarking Multimodal AutoML for Tabular Data with Text Fields. CoRR Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
2021	A*	`conf`	Continuous Doubly Constrained Batch Reinforcement Learning. NeurIPS Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola
2021	J	`jnl`	Continuous Doubly Constrained Batch Reinforcement Learning. CoRR Rasool Fakoor, Jonas Mueller, Pratik Chaudhari, Alexander J. Smola
2021	J	`jnl`	Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features. CoRR Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
2021	A*	`conf`	Deep Extended Hazard Models for Survival Analysis. NeurIPS Qixian Zhong, Jonas Mueller, Jane-Ling Wang
2021	A*	`conf`	Deep Learning for Functional Data Analysis with Adaptive Basis Layers. ICML Junwen Yao, Jonas Mueller, Jane-Ling Wang
2021	J	`jnl`	Deep Learning for Functional Data Analysis with Adaptive Basis Layers. CoRR Junwen Yao, Jonas Mueller, Jane-Ling Wang
2021	J	`jnl`	Deep Quantile Aggregation. CoRR Taesup Kim, Rasool Fakoor, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani
2021	—	`conf`	Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. SustaiNLP@EMNLP Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
2021	J	`jnl`	Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. CoRR Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
2021	A*	`conf`	Overinterpretation reveals image classification model pathologies. NeurIPS Brandon Carter, Siddhartha Jain, Jonas Mueller, David Gifford
2021	—	`conf`	Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks. NeurIPS Datasets and Benchmarks Curtis G. Northcutt, Anish Athalye, Jonas Mueller
2021	J	`jnl`	Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks. CoRR Curtis G. Northcutt, Anish Athalye, Jonas Mueller
2020	J	`jnl`	Antibody complementarity determining region design using high-capacity machine learning. Bioinform. Ge Liu, Haoyang Zeng, Jonas Mueller, Brandon Carter, Ziheng Wang, Jonas Schilz, Geraldine Horny, Michael E. Birnbaum, Stefan Ewert, David K. Gifford
2020	J	`jnl`	AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data. CoRR Nick Erickson, Jonas Mueller, Alexander Shirkov, Hang Zhang, Pedro Larroy, Mu Li, Alexander J. Smola
2020	A*	`conf`	Educating Text Autoencoders: Latent Representation Guidance via Denoising. ICML Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi S. Jaakkola
2020	A*	`conf`	Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. NeurIPS Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
2020	J	`jnl`	Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. CoRR Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
2020	A*	`conf`	Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data. KDD Jonas Mueller, Xingjian Shi, Alexander J. Smola
2020	A*	`conf`	Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles. AAAI Siddhartha Jain, Ge Liu, Jonas Mueller, David Gifford
2020	J	`jnl`	Overinterpretation reveals image classification model pathologies. CoRR Brandon Carter, Siddhartha Jain, Jonas Mueller, David K. Gifford
2020	J	`jnl`	ResNeSt: Split-Attention Networks. CoRR Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Mueller, R. Manmatha, Mu Li, Alexander J. Smola
2020	J	`jnl`	TraDE: Transformers for Density Estimation. CoRR Rasool Fakoor, Pratik Chaudhari, Jonas Mueller, Alexander J. Smola
2019	—	`conf`	IMaT: Unsupervised Text Attribute Transfer via Iterative Matching and Translation. EMNLP/IJCNLP (1) Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews, Enrico Santus
2019	J	`jnl`	Latent Space Secrets of Denoising Text-Autoencoders. CoRR Tianxiao Shen, Jonas Mueller, Regina Barzilay, Tommi S. Jaakkola
2019	A*	`conf`	Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing. NeurIPS Jonas Mueller, Vasilis Syrgkanis, Matt Taddy
2019	J	`jnl`	Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles. CoRR Siddhartha Jain, Ge Liu, Jonas Mueller, David K. Gifford
2019	A*	`conf`	Recognizing Variables from Their Data via Deep Embeddings of Distributions. ICDM Jonas Mueller, Alex Smola
2019	J	`jnl`	Recognizing Variables from their Data via Deep Embeddings of Distributions. CoRR Jonas Mueller, Alex Smola
2019	J	`jnl`	Unsupervised Text Style Transfer via Iterative Matching and Translation. CoRR Zhijing Jin, Di Jin, Jonas Mueller, Nicholas Matthews, Enrico Santus
2019	A	`conf`	What made you do this? Understanding black-box decisions with sufficient input subsets. AISTATS Brandon Carter, Jonas Mueller, Siddhartha Jain, David K. Gifford
2018	—	`—`	Flexible models for understanding and optimizing complex populations. Jonas Mueller
2018	J	`jnl`	Low-rank Bandit Methods for High-dimensional Dynamic Pricing. CoRR Jonas Mueller, Vasilis Syrgkanis, Matt Taddy
2018	J	`jnl`	What made you do this? Understanding black-box decisions with sufficient input subsets. CoRR Brandon Carter, Jonas Mueller, Siddhartha Jain, David K. Gifford
2017	A	`conf`	Learning Optimal Interventions. AISTATS Jonas Mueller, David Reshef, George Du, Tommi S. Jaakkola
2017	A*	`conf`	Sequence to Better Sequence: Continuous Revision of Combinatorial Structures. ICML Jonas Mueller, David K. Gifford, Tommi S. Jaakkola
2016	J	`jnl`	Learning Optimal Interventions. CoRR Jonas Mueller, David Reshef, George Du, Tommi S. Jaakkola
2016	A*	`conf`	Siamese Recurrent Architectures for Learning Sentence Similarity. AAAI Jonas Mueller, Aditya Thyagarajan
2015	—	`conf`	Principal Differences Analysis: Interpretable Characterization of Differences between Distributions. NIPS Jonas Mueller, Tommi S. Jaakkola
2015	J	`jnl`	Principal Differences Analysis: Interpretable Characterization of Differences between Distributions. CoRR Jonas Mueller, Tommi S. Jaakkola