Timezone: »
Author Information
Thomas Dietterich ((organization))
Chelsea Finn (Stanford)
Chelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University. Finn's research interests lie in the capability of robots and other agents to develop broadly intelligent behavior through learning and interaction. To this end, her work has included deep learning algorithms for concurrently learning visual perception and control in robotic manipulation skills, inverse reinforcement methods for learning reward functions underlying behavior, and meta-learning algorithms that can enable fast, few-shot adaptation in both visual perception and deep reinforcement learning. Finn received her Bachelor's degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, the Microsoft Research Faculty Fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across four universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.
Kamalika Chaudhuri (University of California at San Diego)
Yarin Gal (University of Oxford)
Uri Shalit (Technion)
More from the Same Authors
-
2021 : A Practical Notation for Information-Theoretic Quantities between Outcomes and Random Variables »
Andreas Kirsch · Yarin Gal -
2021 : GoldiProx Selection: Faster training by learning what is learnable, not yet learned, and worth learning »
Sören Mindermann · Muhammed Razzak · Adrien Morisot · Aidan Gomez · Sebastian Farquhar · Jan Brauner · Yarin Gal -
2021 : Active Learning under Pool Set Distribution Shift and Noisy Data »
Andreas Kirsch · Tom Rainforth · Yarin Gal -
2021 : Batch Active Learning with Stochastic Acquisition Functions »
Andreas Kirsch · Sebastian Farquhar · Yarin Gal -
2021 : Understanding Instance-based Interpretability of Variational Auto-Encoders »
· Zhifeng Kong · Kamalika Chaudhuri -
2021 : On Low Rank Training of Deep Neural Networks »
Siddhartha Kamalakara · Acyr Locatelli · Bharat Venkitesh · Jimmy Ba · Yarin Gal · Aidan Gomez -
2021 : Privacy Amplification by Bernoulli Sampling »
Jacob Imola · Kamalika Chaudhuri -
2021 : A Shuffling Framework For Local Differential Privacy »
Casey M Meehan · Amrita Roy Chowdhury · Kamalika Chaudhuri · Somesh Jha -
2021 : Privacy Amplification by Subsampling in Time Domain »
Tatsuki Koga · Casey M Meehan · Kamalika Chaudhuri -
2021 : Multi-Task Offline Reinforcement Learning with Conservative Data Sharing »
Tianhe (Kevin) Yu · Aviral Kumar · Yevgen Chebotar · Karol Hausman · Sergey Levine · Chelsea Finn -
2021 : Visual Adversarial Imitation Learning using Variational Models »
Rafael Rafailov · Tianhe (Kevin) Yu · Aravind Rajeswaran · Chelsea Finn -
2021 : Intrinsic Control of Variational Beliefs in Dynamic Partially-Observed Visual Environments »
Nicholas Rhinehart · Jenny Wang · Glen Berseth · John Co-Reyes · Danijar Hafner · Chelsea Finn · Sergey Levine -
2021 : The Reflective Explorer: Online Meta-Exploration from Offline Data in Visual Tasks with Sparse Rewards »
Rafael Rafailov · Varun Kumar · Tianhe (Kevin) Yu · Avi Singh · mariano phielipp · Chelsea Finn -
2021 : Multi-Task Offline Reinforcement Learning with Conservative Data Sharing »
Tianhe (Kevin) Yu · Aviral Kumar · Yevgen Chebotar · Karol Hausman · Sergey Levine · Chelsea Finn -
2021 : Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data »
Andrew Jesson · Panagiotis Tigas · Joost van Amersfoort · Andreas Kirsch · Uri Shalit · Yarin Gal -
2021 : A Simple Baseline for Batch Active Learning with Stochastic Acquisition Functions »
Andreas Kirsch · Sebastian Farquhar · Yarin Gal -
2021 : Active Learning under Pool Set Distribution Shift and Noisy Data »
Andreas Kirsch · Tom Rainforth · Yarin Gal -
2022 : Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models »
Eric Mitchell · Peter Henderson · Christopher Manning · Dan Jurafsky · Chelsea Finn -
2022 : Giving Complex Feedback in Online Student Learning with Meta-Exploration »
Evan Liu · Moritz Stephan · Allen Nie · Chris Piech · Emma Brunskill · Chelsea Finn -
2022 : Policy Architectures for Compositional Generalization in Control »
Allan Zhou · Vikash Kumar · Chelsea Finn · Aravind Rajeswaran -
2022 : Diversify and Disambiguate: Learning from Underspecified Data »
Yoonho Lee · Huaxiu Yao · Chelsea Finn -
2022 : Understanding Rare Spurious Correlations in Neural Networks »
Yao-Yuan Yang · Chi-Ning Chou · Kamalika Chaudhuri -
2022 : Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time »
Huaxiu Yao · Caroline Choi · Yoonho Lee · Pang Wei Koh · Chelsea Finn -
2022 : Giving Feedback on Interactive Student Programs with Meta-Exploration »
Evan Liu · Moritz Stephan · Allen Nie · Chris Piech · Emma Brunskill · Chelsea Finn -
2022 : When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning »
Annie Xie · Fahim Tajwar · Archit Sharma · Chelsea Finn -
2022 : You Only Live Once: Single-Life Reinforcement Learning via Learned Reward Shaping »
Annie Chen · Archit Sharma · Sergey Levine · Chelsea Finn -
2022 : Diversify and Disambiguate: Learning from Underspecified Data »
Yoonho Lee · Huaxiu Yao · Chelsea Finn -
2022 : Plex: Towards Reliability using Pretrained Large Model Extensions »
Dustin Tran · Andreas Kirsch · Balaji Lakshminarayanan · Huiyi Hu · Du Phan · D. Sculley · Jasper Snoek · Jeremiah Liu · Jie Ren · Joost van Amersfoort · Kehang Han · E. Kelly Buchanan · Kevin Murphy · Mark Collier · Mike Dusenberry · Neil Band · Nithum Thain · Rodolphe Jenatton · Tim G. J Rudner · Yarin Gal · Zachary Nado · Zelda Mariet · Zi Wang · Zoubin Ghahramani -
2022 : Self-Destructing Models: Increasing the Costs of Harmful Dual Uses in Foundation Models »
Eric Mitchell · Peter Henderson · Christopher Manning · Dan Jurafsky · Chelsea Finn -
2022 : Plex: Towards Reliability using Pretrained Large Model Extensions »
Dustin Tran · Andreas Kirsch · Balaji Lakshminarayanan · Huiyi Hu · Du Phan · D. Sculley · Jasper Snoek · Jeremiah Liu · JIE REN · Joost van Amersfoort · Kehang Han · Estefany Kelly Buchanan · Kevin Murphy · Mark Collier · Michael Dusenberry · Neil Band · Nithum Thain · Rodolphe Jenatton · Tim G. J Rudner · Yarin Gal · Zachary Nado · Zelda Mariet · Zi Wang · Zoubin Ghahramani -
2023 : In-Context Decision-Making from Supervised Pretraining »
Jonathan Lee · Annie Xie · Aldo Pacchiano · Yash Chandak · Chelsea Finn · Ofir Nachum · Emma Brunskill -
2023 : Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware »
Tony Zhao · Vikash Kumar · Sergey Levine · Chelsea Finn -
2023 : Machine Learning with Feature Differential Privacy »
Saeed Mahloujifar · Chuan Guo · G. Edward Suh · Kamalika Chaudhuri -
2023 : BatchGFN: Generative Flow Networks for Batch Active Learning »
Shreshth Malik · Salem Lahlou · Andrew Jesson · Moksh Jain · Nikolay Malkin · Tristan Deleu · Yoshua Bengio · Yarin Gal -
2023 : CLAM: Selective Clarification for Ambiguous Questions with Generative Language Models »
Lorenz Kuhn · Yarin Gal · Sebastian Farquhar -
2023 : Direct Preference Optimization: Your Language Model is Secretly a Reward Model »
Rafael Rafailov · Archit Sharma · Eric Mitchell · Stefano Ermon · Christopher Manning · Chelsea Finn -
2023 : Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning »
Mitsuhiko Nakamoto · Yuexiang Zhai · Anikait Singh · Max Sobol Mark · Yi Ma · Chelsea Finn · Aviral Kumar · Sergey Levine -
2023 : Keynote I: Detecting and Adapting to Distribution Shift »
Chelsea Finn -
2023 Workshop: The Second Workshop on Spurious Correlations, Invariance and Stability »
Yoav Wald · Claudia Shi · Aahlad Puli · Amir Feder · Limor Gultchin · Mark Goldstein · Maggie Makar · Victor Veitch · Uri Shalit -
2023 : Panel Discussion »
Peter Kairouz · Song Han · Kamalika Chaudhuri · Florian Tramer -
2023 : Kamalika Chaudhuri »
Kamalika Chaudhuri -
2023 Poster: DiscoBAX - Discovery of optimal intervention sets in genomic experiment design »
Clare Lyle · Arash Mehrjou · Pascal Notin · Andrew Jesson · Stefan Bauer · Yarin Gal · Patrick Schwab -
2023 Poster: Privacy-Aware Compression for Federated Learning Through Numerical Mechanism Design »
Chuan Guo · Kamalika Chaudhuri · Pierre Stock · Michael Rabbat -
2023 Oral: DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature »
Eric Mitchell · Yoonho Lee · Alexander Khazatsky · Christopher Manning · Chelsea Finn -
2023 Poster: Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning »
Evan Liu · Sahaana Suri · Tong Mu · Allan Zhou · Chelsea Finn -
2023 Poster: DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature »
Eric Mitchell · Yoonho Lee · Alexander Khazatsky · Christopher Manning · Chelsea Finn -
2023 Poster: Differentiable Multi-Target Causal Bayesian Experimental Design »
Panagiotis Tigas · Yashas Annadani · Desi Ivanova · Andrew Jesson · Yarin Gal · Adam Foster · Stefan Bauer -
2023 Oral: Why does Throwing Away Data Improve Worst-Group Error? »
Kamalika Chaudhuri · Kartik Ahuja · Martin Arjovsky · David Lopez-Paz -
2023 Poster: B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding »
Miruna Oprescu · Jacob Dorn · Marah Ghoummaid · Andrew Jesson · Nathan Kallus · Uri Shalit -
2023 Poster: Data-Copying in Generative Models: A Formal Framework »
Robi Bhattacharjee · Sanjoy Dasgupta · Kamalika Chaudhuri -
2023 Poster: A Two-Stage Active Learning Algorithm for k-Nearest Neighbors »
Nicholas Rittler · Kamalika Chaudhuri -
2023 Poster: Why does Throwing Away Data Improve Worst-Group Error? »
Kamalika Chaudhuri · Kartik Ahuja · Martin Arjovsky · David Lopez-Paz -
2022 : Plex: Towards Reliability using Pretrained Large Model Extensions »
Dustin Tran · Andreas Kirsch · Balaji Lakshminarayanan · Huiyi Hu · Du Phan · D. Sculley · Jasper Snoek · Jeremiah Liu · JIE REN · Joost van Amersfoort · Kehang Han · Estefany Kelly Buchanan · Kevin Murphy · Mark Collier · Michael Dusenberry · Neil Band · Nithum Thain · Rodolphe Jenatton · Tim G. J Rudner · Yarin Gal · Zachary Nado · Zelda Mariet · Zi Wang · Zoubin Ghahramani -
2022 : Giving Complex Feedback in Online Student Learning with Meta-Exploration »
Evan Liu · Moritz Stephan · Allen Nie · Chris Piech · Emma Brunskill · Chelsea Finn -
2022 Workshop: The First Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward »
Huaxiu Yao · Hugo Larochelle · Percy Liang · Colin Raffel · Jian Tang · Ying WEI · Saining Xie · Eric Xing · Chelsea Finn -
2022 : Panel discussion »
Steffen Schneider · Aleksander Madry · Alexei Efros · Chelsea Finn · Soheil Feizi -
2022 : Q/A: Chelsea Finn »
Chelsea Finn -
2022 : Invited Speaker: Chelsea Finn »
Chelsea Finn -
2022 : Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time »
Huaxiu Yao · Caroline Choi · Yoonho Lee · Pang Wei Koh · Chelsea Finn -
2022 : Invited Talk 3: Chelsea Finn »
Chelsea Finn -
2022 Workshop: Spurious correlations, Invariance, and Stability (SCIS) »
Aahlad Puli · Maggie Makar · Victor Veitch · Yoav Wald · Mark Goldstein · Limor Gultchin · Angela Zhou · Uri Shalit · Suchi Saria -
2022 Poster: Robust Policy Learning over Multiple Uncertainty Sets »
Annie Xie · Shagun Sodhani · Chelsea Finn · Joelle Pineau · Amy Zhang -
2022 Poster: How to Leverage Unlabeled Data in Offline Reinforcement Learning »
Tianhe (Kevin) Yu · Aviral Kumar · Yevgen Chebotar · Karol Hausman · Chelsea Finn · Sergey Levine -
2022 Poster: Learning Dynamics and Generalization in Deep Reinforcement Learning »
Clare Lyle · Mark Rowland · Will Dabney · Marta Kwiatkowska · Yarin Gal -
2022 Poster: Memory-Based Model Editing at Scale »
Eric Mitchell · Charles Lin · Antoine Bosselut · Christopher Manning · Chelsea Finn -
2022 Poster: Continual Learning via Sequential Function-Space Variational Inference »
Tim G. J Rudner · Freddie Bickford Smith · QIXUAN FENG · Yee-Whye Teh · Yarin Gal -
2022 Poster: Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt »
Sören Mindermann · Jan Brauner · Muhammed Razzak · Mrinank Sharma · Andreas Kirsch · Winnie Xu · Benedikt Höltgen · Aidan Gomez · Adrien Morisot · Sebastian Farquhar · Yarin Gal -
2022 Spotlight: Learning Dynamics and Generalization in Deep Reinforcement Learning »
Clare Lyle · Mark Rowland · Will Dabney · Marta Kwiatkowska · Yarin Gal -
2022 Spotlight: Robust Policy Learning over Multiple Uncertainty Sets »
Annie Xie · Shagun Sodhani · Chelsea Finn · Joelle Pineau · Amy Zhang -
2022 Spotlight: How to Leverage Unlabeled Data in Offline Reinforcement Learning »
Tianhe (Kevin) Yu · Aviral Kumar · Yevgen Chebotar · Karol Hausman · Chelsea Finn · Sergey Levine -
2022 Spotlight: Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt »
Sören Mindermann · Jan Brauner · Muhammed Razzak · Mrinank Sharma · Andreas Kirsch · Winnie Xu · Benedikt Höltgen · Aidan Gomez · Adrien Morisot · Sebastian Farquhar · Yarin Gal -
2022 Spotlight: Continual Learning via Sequential Function-Space Variational Inference »
Tim G. J Rudner · Freddie Bickford Smith · QIXUAN FENG · Yee-Whye Teh · Yarin Gal -
2022 Spotlight: Memory-Based Model Editing at Scale »
Eric Mitchell · Charles Lin · Antoine Bosselut · Christopher Manning · Chelsea Finn -
2022 Poster: Thompson Sampling for Robust Transfer in Multi-Task Bandits »
Zhi Wang · Chicheng Zhang · Kamalika Chaudhuri -
2022 Poster: Improving Out-of-Distribution Robustness via Selective Augmentation »
Huaxiu Yao · Yu Wang · Sai Li · Linjun Zhang · Weixin Liang · James Zou · Chelsea Finn -
2022 Poster: Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval »
Pascal Notin · Mafalda Dias · Jonathan Frazer · Javier Marchena Hurtado · Aidan Gomez · Debora Marks · Yarin Gal -
2022 Spotlight: Thompson Sampling for Robust Transfer in Multi-Task Bandits »
Zhi Wang · Chicheng Zhang · Kamalika Chaudhuri -
2022 Spotlight: Improving Out-of-Distribution Robustness via Selective Augmentation »
Huaxiu Yao · Yu Wang · Sai Li · Linjun Zhang · Weixin Liang · James Zou · Chelsea Finn -
2022 Spotlight: Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval »
Pascal Notin · Mafalda Dias · Jonathan Frazer · Javier Marchena Hurtado · Aidan Gomez · Debora Marks · Yarin Gal -
2022 Poster: Bounding Training Data Reconstruction in Private (Deep) Learning »
Chuan Guo · Brian Karrer · Kamalika Chaudhuri · Laurens van der Maaten -
2022 Poster: A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning »
Archit Sharma · Rehaan Ahmad · Chelsea Finn -
2022 Poster: Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations »
Michael Zhang · Nimit Sohoni · Hongyang Zhang · Chelsea Finn · Christopher Re -
2022 Oral: Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations »
Michael Zhang · Nimit Sohoni · Hongyang Zhang · Chelsea Finn · Christopher Re -
2022 Spotlight: A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning »
Archit Sharma · Rehaan Ahmad · Chelsea Finn -
2022 Oral: Bounding Training Data Reconstruction in Private (Deep) Learning »
Chuan Guo · Brian Karrer · Kamalika Chaudhuri · Laurens van der Maaten -
2021 : Active Learning under Pool Set Distribution Shift and Noisy Data »
Yarin Gal · Tom Rainforth · Andreas Kirsch -
2021 : Discussion Panel #2 »
Bo Li · Nicholas Carlini · Andrzej Banburski · Kamalika Chaudhuri · Will Xiao · Cihang Xie -
2021 : Invited Talk #9 »
Kamalika Chaudhuri -
2021 : Invited Talk: Kamalika Chaudhuri »
Kamalika Chaudhuri -
2021 : Invited Talk #1 »
Yarin Gal -
2021 : Invited Talk: Kamalika Chaudhuri »
Kamalika Chaudhuri -
2021 Workshop: The Neglected Assumptions In Causal Inference »
Niki Kilbertus · Lily Hu · Laura Balzer · Uri Shalit · Alexander D'Amour · Razieh Nabi -
2021 : RL Foundation Panel »
Matthew Botvinick · Thomas Dietterich · Leslie Kaelbling · John Langford · Warrren B Powell · Csaba Szepesvari · Lihong Li · Yuxi Li -
2021 Poster: Offline Meta-Reinforcement Learning with Advantage Weighting »
Eric Mitchell · Rafael Rafailov · Xue Bin Peng · Sergey Levine · Chelsea Finn -
2021 Poster: WILDS: A Benchmark of in-the-Wild Distribution Shifts »
Pang Wei Koh · Shiori Sagawa · Henrik Marklund · Sang Michael Xie · Marvin Zhang · Akshay Balsubramani · Weihua Hu · Michihiro Yasunaga · Richard Lanas Phillips · Irena Gao · Tony Lee · Etienne David · Ian Stavness · Wei Guo · Berton Earnshaw · Imran Haque · Sara Beery · Jure Leskovec · Anshul Kundaje · Emma Pierson · Sergey Levine · Chelsea Finn · Percy Liang -
2021 Spotlight: Offline Meta-Reinforcement Learning with Advantage Weighting »
Eric Mitchell · Rafael Rafailov · Xue Bin Peng · Sergey Levine · Chelsea Finn -
2021 Oral: WILDS: A Benchmark of in-the-Wild Distribution Shifts »
Pang Wei Koh · Shiori Sagawa · Henrik Marklund · Sang Michael Xie · Marvin Zhang · Akshay Balsubramani · Weihua Hu · Michihiro Yasunaga · Richard Lanas Phillips · Irena Gao · Tony Lee · Etienne David · Ian Stavness · Wei Guo · Berton Earnshaw · Imran Haque · Sara Beery · Jure Leskovec · Anshul Kundaje · Emma Pierson · Sergey Levine · Chelsea Finn · Percy Liang -
2021 Poster: Active Testing: Sample-Efficient Model Evaluation »
Jannik Kossen · Sebastian Farquhar · Yarin Gal · Tom Rainforth -
2021 Poster: On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes »
Tim G. J. Rudner · Oscar Key · Yarin Gal · Tom Rainforth -
2021 Spotlight: Active Testing: Sample-Efficient Model Evaluation »
Jannik Kossen · Sebastian Farquhar · Yarin Gal · Tom Rainforth -
2021 Spotlight: On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes »
Tim G. J. Rudner · Oscar Key · Yarin Gal · Tom Rainforth -
2021 Poster: Sample Complexity of Robust Linear Classification on Separated Data »
Robi Bhattacharjee · Somesh Jha · Kamalika Chaudhuri -
2021 Poster: Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding »
Andrew Jesson · Sören Mindermann · Yarin Gal · Uri Shalit -
2021 Spotlight: Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding »
Andrew Jesson · Sören Mindermann · Yarin Gal · Uri Shalit -
2021 Spotlight: Sample Complexity of Robust Linear Classification on Separated Data »
Robi Bhattacharjee · Somesh Jha · Kamalika Chaudhuri -
2021 Poster: Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression »
Junhyung Park · Uri Shalit · Bernhard Schölkopf · Krikamol Muandet -
2021 Poster: Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices »
Evan Liu · Aditi Raghunathan · Percy Liang · Chelsea Finn -
2021 Spotlight: Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression »
Junhyung Park · Uri Shalit · Bernhard Schölkopf · Krikamol Muandet -
2021 Spotlight: Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices »
Evan Liu · Aditi Raghunathan · Percy Liang · Chelsea Finn -
2021 Poster: Just Train Twice: Improving Group Robustness without Training Group Information »
Evan Liu · Behzad Haghgoo · Annie Chen · Aditi Raghunathan · Pang Wei Koh · Shiori Sagawa · Percy Liang · Chelsea Finn -
2021 Poster: Connecting Interpretability and Robustness in Decision Trees through Separation »
Michal Moshkovitz · Yao-Yuan Yang · Kamalika Chaudhuri -
2021 Poster: PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning »
Angelos Filos · Clare Lyle · Yarin Gal · Sergey Levine · Natasha Jaques · Gregory Farquhar -
2021 Oral: Just Train Twice: Improving Group Robustness without Training Group Information »
Evan Liu · Behzad Haghgoo · Annie Chen · Aditi Raghunathan · Pang Wei Koh · Shiori Sagawa · Percy Liang · Chelsea Finn -
2021 Spotlight: Connecting Interpretability and Robustness in Decision Trees through Separation »
Michal Moshkovitz · Yao-Yuan Yang · Kamalika Chaudhuri -
2021 Oral: PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning »
Angelos Filos · Clare Lyle · Yarin Gal · Sergey Levine · Natasha Jaques · Gregory Farquhar -
2021 Poster: Deep Reinforcement Learning amidst Continual Structured Non-Stationarity »
Annie Xie · James Harrison · Chelsea Finn -
2021 Spotlight: Deep Reinforcement Learning amidst Continual Structured Non-Stationarity »
Annie Xie · James Harrison · Chelsea Finn -
2020 : Invited Talk 11: Prof. Chelsea Finn from Stanford University »
Chelsea Finn -
2020 Poster: Robust Learning with the Hilbert-Schmidt Independence Criterion »
Daniel Greenfeld · Uri Shalit -
2020 Poster: Inter-domain Deep Gaussian Processes »
Tim G. J. Rudner · Dino Sejdinovic · Yarin Gal -
2020 Poster: Goal-Aware Prediction: Learning to Model What Matters »
Suraj Nair · Silvio Savarese · Chelsea Finn -
2020 Poster: On the Expressivity of Neural Networks for Deep Reinforcement Learning »
Kefan Dong · Yuping Luo · Tianhe (Kevin) Yu · Chelsea Finn · Tengyu Ma -
2020 Poster: Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? »
Angelos Filos · Panagiotis Tigas · Rowan McAllister · Nicholas Rhinehart · Sergey Levine · Yarin Gal -
2020 Poster: Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings »
Jesse Zhang · Brian Cheung · Chelsea Finn · Sergey Levine · Dinesh Jayaraman -
2020 Poster: Invariant Causal Prediction for Block MDPs »
Amy Zhang · Clare Lyle · Shagun Sodhani · Angelos Filos · Marta Kwiatkowska · Joelle Pineau · Yarin Gal · Doina Precup -
2020 Poster: Uncertainty Estimation Using a Single Deep Deterministic Neural Network »
Joost van Amersfoort · Lewis Smith · Yee-Whye Teh · Yarin Gal -
2020 Poster: When are Non-Parametric Methods Robust? »
Robi Bhattacharjee · Kamalika Chaudhuri -
2019 : Panel Discussion (moderator: Tom Dietterich) »
Max Welling · Kilian Weinberger · Terrance Boult · Dawn Song · Thomas Dietterich -
2019 Talk: Opening Remarks »
Kamalika Chaudhuri · Ruslan Salakhutdinov -
2018 Poster: Active Learning with Logged Data »
Songbai Yan · Kamalika Chaudhuri · Tara Javidi -
2018 Poster: Analyzing the Robustness of Nearest Neighbors to Adversarial Examples »
Yizhen Wang · Somesh Jha · Kamalika Chaudhuri -
2018 Oral: Active Learning with Logged Data »
Songbai Yan · Kamalika Chaudhuri · Tara Javidi -
2018 Oral: Analyzing the Robustness of Nearest Neighbors to Adversarial Examples »
Yizhen Wang · Somesh Jha · Kamalika Chaudhuri -
2018 Poster: Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning »
Thomas Dietterich · George Trimponias · Zhitang Chen -
2018 Poster: Open Category Detection with PAC Guarantees »
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks -
2018 Poster: Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam »
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava -
2018 Oral: Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning »
Thomas Dietterich · George Trimponias · Zhitang Chen -
2018 Oral: Open Category Detection with PAC Guarantees »
Si Liu · Risheek Garrepalli · Thomas Dietterich · Alan Fern · Dan Hendrycks -
2018 Oral: Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam »
Mohammad Emtiyaz Khan · Didrik Nielsen · Voot Tangkaratt · Wu Lin · Yarin Gal · Akash Srivastava -
2017 Workshop: Picky Learners: Choosing Alternative Ways to Process Data. »
Corinna Cortes · Kamalika Chaudhuri · Giulia DeSalvo · Ningshan Zhang · Chicheng Zhang -
2017 Poster: Active Heteroscedastic Regression »
Kamalika Chaudhuri · Prateek Jain · Nagarajan Natarajan -
2017 Talk: Active Heteroscedastic Regression »
Kamalika Chaudhuri · Prateek Jain · Nagarajan Natarajan