Jimmy Ba

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 95

Top Venues

Publications

Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text. ICLR (2024)
Nathaniel Li, Alexander Pan, Anjali Gopal, Summer Yue, Daniel Berrios, Alice Gatti, Justin D. Li, Ann-Kathrin Dombrowski, Shashwat Goel, Long Phan, Gabriel Mukobi, Nathan Helm-Burger, Rassin Lababidi, Lennart Justen, Andrew B. Liu, Michael Chen, Isabelle Barrass, Oliver Zhang, Xiaoyuan Zhu, Rishub Tamirisa, Bhrugu Bharathi, Adam Khoja, Zhenqi Zhao, Ariel Herbert-Voss, Cort B. Breuer, Andy Zou, Mantas Mazeika, Zifan Wang, Palash Oswal, Weiran Liu, Adam A. Hunt, Justin Tienken-Harder, Kevin Y. Shih, Kemper Talley, John Guan, Russell Kaplan, Ian Steneker, David Campbell, Brad Jokubaitis, Alex Levinson, Jean Wang, William Qian, Kallol Krishna Karmakar, Steven Basart, Stephen Fitz, Mindy Levine, Ponnurangam Kumaraguru, Uday Kiran Tupakula, Vijay Varadharajan, Yan Shoshitaishvili, Jimmy Ba, Kevin M. Esvelt, Alexandr Wang, Dan Hendrycks
The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning. CoRR (2024)
Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. ICLR (2024)
Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
Decomposed Prompting to Answer Questions on a Course Discussion Board. CoRR (2024)
Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, Jimmy Ba, Amjad Almahairi
Residual Prompt Tuning: Improving Prompt Tuning with Residual Reparameterization. CoRR (2023)
Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. CoRR (2023)
Augustin Toma, Patrick R. Lawler, Jimmy Ba, Rahul G. Krishnan, Barry B. Rubin, Bo Wang
Clinical Camel: An Open-Source Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding. CoRR (2023)
Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. CoRR (2023)
Paul Zhang, Brandon Jaipersaud, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
Classifying Course Discussion Board Questions using LLMs. ITiCSE (2) (2023)
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba
Large Language Models are Human-Level Prompt Engineers. ICLR (2023)
Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. CoRR (2023)
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu
Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective. NeurIPS (2023)
Michael R. Zhang, Nishkrit Desai, Juhan Bae, Jonathan Lorraine, Jimmy Ba
Using Large Language Models for Hyperparameter Optimization. CoRR (2023)
Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba
Boosted Prompt Ensembles for Large Language Models. CoRR (2023)
Shalev Lifshitz, Keiran Paster, Harris Chan, Jimmy Ba, Sheila A. McIlraith
STEVE-1: A Generative Model for Text-to-Behavior in Minecraft. NeurIPS (2023)
Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. CoRR (2023)
Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy P. Lillicrap
Mastering Diverse Domains through World Models. CoRR (2023)
Zhaoyan Liu, Noël Vouitsis, Satya Krishna Gorti, Jimmy Ba, Gabriel Loaiza-Ganem
TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation. ICML (2023)
Anastasia Razdaibiedina, Yuning Mao, Madian Khabsa, Mike Lewis, Rui Hou, Jimmy Ba, Amjad Almahairi
Residual Prompt Tuning: improving prompt tuning with residual reparameterization. ACL (Findings) (2023)
Brandon Jaipersaud, Paul Zhang, Jimmy Ba, Andrew Petersen, Lisa Zhang, Michael R. Zhang
Decomposed Prompting to Answer Questions on a Course Discussion Board. AIED (Posters/Late Breaking Results/...) (2023)
Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Baker Grosse
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. ICLR (2023)
Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text. CoRR (2023)
Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. NeurIPS (2023)
Yongchao Zhou, Hshmat Sahak, Jimmy Ba
Training on Thin Air: Improve Image Classification with Generated Data. CoRR (2023)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
You Can't Count on Luck: Why Decision Transformers Fail in Stochastic Environments. CoRR (2022)
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba
Large Language Models Are Human-Level Prompt Engineers. CoRR (2022)
Jimmy Ba, Murat A. Erdogdu, Marzyeh Ghassemi, Shengyang Sun, Taiji Suzuki, Denny Wu, Tianzong Zhang
Understanding the Variance Collapse of SVGD in High Dimensions. ICLR (2022)
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. NeurIPS (2022)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments. NeurIPS (2022)
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Zhichao Wang, Denny Wu, Greg Yang
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation. CoRR (2022)
Siddhartha Rao Kamalakara, Acyr Locatelli, Bharat Venkitesh, Jimmy Ba, Yarin Gal, Aidan N. Gomez
Exploring Low Rank Training of Deep Neural Networks. CoRR (2022)
Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
Dataset Distillation using Neural Feature Regression. CoRR (2022)
Yongchao Zhou, Ehsan Nezhadarya, Jimmy Ba
Dataset Distillation using Neural Feature Regression. NeurIPS (2022)
Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger B. Grosse
Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve. CoRR (2022)
Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. CoRR (2021)
Jingling Li, Mozhi Zhang, Keyulu Xu, John Dickerson, Jimmy Ba
How does a Neural Network's Architecture Impact its Robustness to Noisy Labels? NeurIPS (2021)
Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. CoRR (2021)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
Planning from Pixels using Inverse Dynamics Models. ICLR (2021)
Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba
Mastering Atari with Discrete World Models. ICLR (2021)
Vaibhav Saxena, Jimmy Ba, Danijar Hafner
Clockwork Variational Autoencoders. NeurIPS (2021)
Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba
Learning Domain Invariant Representations in Goal-conditioned Block MDPs. NeurIPS (2021)
Shun-ichi Amari, Jimmy Ba, Roger Baker Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu
When does preconditioning help or hurt generalization? ICLR (2021)
Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba
Efficient Statistical Tests: A Neural Tangent Kernel Approach. ICML (2021)
Yuhuai Wu, Albert Jiang, Jimmy Ba, Roger Baker Grosse
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. ICLR (2021)
Vaibhav Saxena, Jimmy Ba, Danijar Hafner
Clockwork Variational Autoencoders. CoRR (2021)
Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. ICML (2021)
Xiao Shi Huang, Felipe Pérez, Jimmy Ba, Maksims Volkovs
Improving Transformer Optimization Through Better Initialization. ICML (2020)
Jimmy Ba, Murat A. Erdogdu, Taiji Suzuki, Denny Wu, Tianzong Zhang
Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint. ICLR (2020)
Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi
Dream to Control: Learning Behaviors by Latent Imagination. ICLR (2020)
Fartash Faghri, David Duvenaud, David J. Fleet, Jimmy Ba
A Study of Gradient Variance in Deep Learning. CoRR (2020)
Keiran Paster, Sheila A. McIlraith, Jimmy Ba
Planning from Pixels using Inverse Dynamics Models. CoRR (2020)
Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. ICLR (2020)
Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl J. Friston, Nicolas Heess
Action and Perception as Divergence Minimization. CoRR (2020)
Brendon Matusch, Jimmy Ba, Danijar Hafner
Evaluating Agents without Rewards. CoRR (2020)
Shun-ichi Amari, Jimmy Ba, Roger B. Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu
When Does Preconditioning Help or Hurt Generalization? CoRR (2020)
Yeming Wen, Dustin Tran, Jimmy Ba
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning. CoRR (2020)
Yuhuai Wu, Honghua Dong, Roger B. Grosse, Jimmy Ba
The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning. CoRR (2020)
Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. ICML (2020)
Yuanhao Wang, Guodong Zhang, Jimmy Ba
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. ICLR (2020)
Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba
Mastering Atari with Discrete World Models. CoRR (2020)
Yuhuai Wu, Albert Jiang, Jimmy Ba, Roger B. Grosse
INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. CoRR (2020)
Jingling Li, Mozhi Zhang, Keyulu Xu, John P. Dickerson, Jimmy Ba
Noisy Labels Can Induce Good Representations. CoRR (2020)
Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. CoRR (2020)
Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. CoRR (2020)
Yeming Wen, Dustin Tran, Jimmy Ba
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning. ICLR (2020)
Tingwu Wang, Jimmy Ba
Exploring Model-based Planning with Policy Networks. ICLR (2020)
Bradly C. Stadie, Lunjun Zhang, Jimmy Ba
Learning Intrinsic Rewards as a Bi-Level Optimization Problem. UAI (2020)
Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise. AISTATS (2020)
Yuanhao Wang, Guodong Zhang, Jimmy Ba
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach. CoRR (2019)
Yeming Wen, Kevin Luk, Maxime Gazeau, Guodong Zhang, Harris Chan, Jimmy Ba
Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise. CoRR (2019)
Harris Chan, Yuhuai Wu, Jamie Kiros, Sanja Fidler, Jimmy Ba
ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning. CoRR (2019)
Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky
Graph Normalizing Flows. NeurIPS (2019)
Michael R. Zhang, James Lucas, Geoffrey E. Hinton, Jimmy Ba
Lookahead Optimizer: k steps forward, 1 step back. CoRR (2019)
Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba
Neural Graph Evolution: Towards Efficient Automatic Robot Design. ICLR (Poster) (2019)
Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba
Benchmarking Model-Based Reinforcement Learning. CoRR (2019)
Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi
Dream to Control: Learning Behaviors by Latent Imagination. CoRR (2019)
Sheng Jia, Jamie Kiros, Jimmy Ba
DOM-Q-NET: Grounded RL on Structured Language. ICLR (Poster) (2019)
Jenny Liu, Aviral Kumar, Jimmy Ba, Jamie Kiros, Kevin Swersky
Graph Normalizing Flows. CoRR (2019)
Michael R. Zhang, James Lucas, Jimmy Ba, Geoffrey E. Hinton
Lookahead Optimizer: k steps forward, 1 step back. NeurIPS (2019)
Sheng Jia, Jamie Kiros, Jimmy Ba
DOM-Q-NET: Grounded RL on Structured Language. CoRR (2019)
Tingwu Wang, Jimmy Ba
Exploring Model-based Planning with Policy Networks. CoRR (2019)
Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba
Neural Graph Evolution: Towards Efficient Automatic Robot Design. CoRR (2019)
James Martens, Jimmy Ba, Matt Johnson
Kronecker-factored Curvature Approximations for Recurrent Neural Networks. ICLR (Poster) (2018)
Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse
Reversible Recurrent Neural Networks. NeurIPS (2018)
Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. CoRR (2018)
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport. NeurIPS (2018)
Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. ICLR (Poster) (2018)
Matthew MacKay, Paul Vicol, Jimmy Ba, Roger B. Grosse
Reversible Recurrent Neural Networks. CoRR (2018)
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn, Jason D. Lee
Solving Approximate Wasserstein GANs to Stationarity. CoRR (2018)
Tingwu Wang, Renjie Liao, Jimmy Ba, Sanja Fidler
NerveNet: Learning Structured Policy with Graph Neural Networks. ICLR (Poster) (2018)
Jimmy Ba, Roger B. Grosse, James Martens
Distributed Second-Order Optimization using Kronecker-Factored Approximations. ICLR (Poster) (2017)
Yuhuai Wu, Elman Mansimov, Roger B. Grosse, Shun Liao, Jimmy Ba
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NIPS (2017)
Yuhuai Wu, Elman Mansimov, Shun Liao, Roger B. Grosse, Jimmy Ba
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation. CoRR (2017)
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
Using Fast Weights to Attend to the Recent Past. NIPS (2016)
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu
Using Fast Weights to Attend to the Recent Past. CoRR (2016)
Jimmy Ba, Volodymyr Mnih, Koray Kavukcuoglu
Multiple Object Recognition with Visual Attention. ICLR (Poster) (2015)
Jimmy Ba, Roger B. Grosse, Ruslan Salakhutdinov, Brendan J. Frey
Learning Wake-Sleep Recurrent Attention Models. CoRR (2015)
Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. CoRR (2015)
Diederik P. Kingma, Jimmy Ba
Adam: A Method for Stochastic Optimization. ICLR (Poster) (2015)
Jimmy Ba, Kevin Swersky, Sanja Fidler, Ruslan Salakhutdinov
Predicting Deep Zero-Shot Convolutional Neural Networks using Textual Descriptions. CoRR (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jimmy Ba