Rebecca Roelofs

According to our database1, Rebecca Roelofs authored at least 29 papers between 2012 and 2024.

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Bibliography

2024
Training Language Models to Self-Correct via Reinforcement Learning.
CoRR, 2024

CausalAgents: A Robustness Benchmark for Motion Forecasting.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
Gemini: A Family of Highly Capable Multimodal Models.
CoRR, 2023

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios.
IROS, 2023

Multi-Agent Reachability Calibration with Conformal Prediction.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning.
Trans. Mach. Learn. Res., 2022

CausalAgents: A Robustness Benchmark for Motion Forecasting using Causal Relationships.
CoRR, 2022

When does dough become a bagel? Analyzing the remaining mistakes on ImageNet.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Spectral Bias in Practice: The Role of Function Frequency in Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.
Proceedings of the International Conference on Machine Learning, 2022

Scene Transformer: A unified architecture for predicting future trajectories of multiple agents.
Proceedings of the Tenth International Conference on Learning Representations, 2022

AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Robust fine-tuning of zero-shot models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Mitigating Bias in Calibration Error Estimation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Scene Transformer: A unified multi-task model for behavior prediction and planning.
CoRR, 2021

Pseudo-labeling for Scalable 3D Object Detection.
CoRR, 2021

Soft Calibration Objectives for Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Do Image Classifiers Generalize Across Time?
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Evaluating Machine Accuracy on ImageNet.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Measuring Generalization and Overfitting in Machine Learning.
PhD thesis, 2019

A systematic framework for natural perturbations from videos.
CoRR, 2019

A Meta-Analysis of Overfitting in Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Do ImageNet Classifiers Generalize to ImageNet?
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
CoRR, 2018

2017
The Marginal Value of Adaptive Gradient Methods in Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sequential operator splitting for constrained nonlinear optimal control.
Proceedings of the 2017 American Control Conference, 2017

2016
Large Scale Kernel Learning using Block Coordinate Descent.
CoRR, 2016

2012
Managing User Requests With the Grand Unified Task System (GUTS).
Proceedings of the Strategies, 2012


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