What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
- Irene Ko
- Pin-Yu Chen
- et al.
- 2024
- ICML 2024
Publications
This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.
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8 results for Luca Daniel
Robust Deep Reinforcement Learning through Adversarial Loss
- Tuomas Oikarinen
- Wang Zhang
- et al.
- 2021
- NeurIPS 2021
One step closer to unbiased aleatoric uncertainty estimation
- Wang Zhang
- Martin Ma
- et al.
- 2024
- AAAI 2024
SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data
- Ching-yun Ko
- Pin-Yu Chen
- et al.
- 2022
- NeurIPS 2022
Fast Convergence for Unstable Reinforcement Learning Problems by Logarithmic Mapping
- Wang Zhang
- Lam Nguyen
- et al.
- 2022
- ICML 2022
On Robustness-Accuracy Characterization of Large Language Models using Synthetic Datasets
- Ching-yun Ko
- Pin-Yu Chen
- et al.
- 2023
- ICML 2023
Guaranteeing Conservation Laws with Projection in Physics-Informed Neural Networks
- Anthony Baez
- Wang Zhang
- et al.
- 2024
- NeurIPS 2024
On Robustness-Accuracy Characterization of Language Models using Synthetic Datasets
- Ching-yun Ko
- Pin-Yu Chen
- et al.
- 2024
- COLM 2024