Jimmy Ba

Orcid: 0009-0000-9062-4180

According to our database1, Jimmy Ba authored at least 80 papers between 2011 and 2024.

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Bibliography

2024
Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries.
CoRR, 2024

The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning.
CoRR, 2024


Identifying the Risks of LM Agents with an LM-Emulated Sandbox.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Using Large Language Models for Hyperparameter Optimization.
CoRR, 2023

Training on Thin Air: Improve Image Classification with Generated Data.
CoRR, 2023

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback.
CoRR, 2023

Clinical Camel: An Open-Source Expert-Level Medical Language Model with Dialogue-Based Knowledge Encoding.
CoRR, 2023

Boosted Prompt Ensembles for Large Language Models.
CoRR, 2023

Mastering Diverse Domains through World Models.
CoRR, 2023

STEVE-1: A Generative Model for Text-to-Behavior in Minecraft.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Classifying Course Discussion Board Questions using LLMs.
Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 2, 2023

TR0N: Translator Networks for 0-Shot Plug-and-Play Conditional Generation.
Proceedings of the International Conference on Machine Learning, 2023

Large Language Models are Human-Level Prompt Engineers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Decomposed Prompting to Answer Questions on a Course Discussion Board.
Proceedings of the Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, 2023

Residual Prompt Tuning: improving prompt tuning with residual reparameterization.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Exploring Low Rank Training of Deep Neural Networks.
CoRR, 2022

You Can't Count on Luck: Why Decision Transformers Fail in Stochastic Environments.
CoRR, 2022

Dataset Distillation using Neural Feature Regression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

You Can't Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Understanding the Variance Collapse of SVGD in High Dimensions.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Clockwork Variational Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How does a Neural Network's Architecture Impact its Robustness to Noisy Labels?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Domain Invariant Representations in Goal-conditioned Block MDPs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Efficient Statistical Tests: A Neural Tangent Kernel Approach.
Proceedings of the 38th International Conference on Machine Learning, 2021

INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving.
Proceedings of the 9th International Conference on Learning Representations, 2021

Planning from Pixels using Inverse Dynamics Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

Mastering Atari with Discrete World Models.
Proceedings of the 9th International Conference on Learning Representations, 2021

When does preconditioning help or hurt generalization?
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Noisy Labels Can Induce Good Representations.
CoRR, 2020

Evaluating Agents without Rewards.
CoRR, 2020

Action and Perception as Divergence Minimization.
CoRR, 2020

A Study of Gradient Variance in Deep Learning.
CoRR, 2020

The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning.
CoRR, 2020

Learning Intrinsic Rewards as a Bi-Level Optimization Problem.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Improving Transformer Optimization Through Better Initialization.
Proceedings of the 37th International Conference on Machine Learning, 2020

BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach.
Proceedings of the 8th International Conference on Learning Representations, 2020

Exploring Model-based Planning with Policy Networks.
Proceedings of the 8th International Conference on Learning Representations, 2020

An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality.
Proceedings of the 8th International Conference on Learning Representations, 2020

Dream to Control: Learning Behaviors by Latent Imagination.
Proceedings of the 8th International Conference on Learning Representations, 2020

Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint.
Proceedings of the 8th International Conference on Learning Representations, 2020

An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Benchmarking Model-Based Reinforcement Learning.
CoRR, 2019

Interplay Between Optimization and Generalization of Stochastic Gradient Descent with Covariance Noise.
CoRR, 2019

ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning.
CoRR, 2019

Lookahead Optimizer: k steps forward, 1 step back.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Graph Normalizing Flows.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Neural Graph Evolution: Towards Efficient Automatic Robot Design.
Proceedings of the 7th International Conference on Learning Representations, 2019

DOM-Q-NET: Grounded RL on Structured Language.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Solving Approximate Wasserstein GANs to Stationarity.
CoRR, 2018

On the Convergence and Robustness of Training GANs with Regularized Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Reversible Recurrent Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches.
Proceedings of the 6th International Conference on Learning Representations, 2018

NerveNet: Learning Structured Policy with Graph Neural Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

Kronecker-factored Curvature Approximations for Recurrent Neural Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Distributed Second-Order Optimization using Kronecker-Factored Approximations.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning.
Proceedings of the 4th International Conference on Learning Representations, 2016

Generating Images from Captions with Attention.
Proceedings of the 4th International Conference on Learning Representations, 2016

Layer Normalization.
CoRR, 2016

Classifying and segmenting microscopy images with deep multiple instance learning.
Bioinform., 2016

Using Fast Weights to Attend to the Recent Past.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning.
CoRR, 2015

Adam: A Method for Stochastic Optimization.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Multiple Object Recognition with Visual Attention.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Learning Wake-Sleep Recurrent Attention Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

"SQUEAKeys": A friction idiophone, for physical interaction with mobile devices.
Proceedings of the 2015 IEEE Games Entertainment Media Conference, 2015

2014
Do Deep Nets Really Need to be Deep?
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Adaptive dropout for training deep neural networks.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2011
User-interfaces based on the water-hammer effect: water-hammer piano as an interactive percussion surface.
Proceedings of the 5th International Conference on Tangible and Embedded Interaction 2011, 2011


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