What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
- Irene Ko
- Pin-Yu Chen
- et al.
- 2024
- ICML 2024
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39 results for Payel Das
Data-Efficient Graph Grammar Learning for Molecular Generation
- Minghao Guo
- Veronika Thost
- et al.
- 2022
- ICLR 2022
Predicting Deep Neural Network Generalization with Perturbation Response Curves
- Yair Schiff
- Brian Quanz
- et al.
- 2021
- NeurIPS 2021
Multi-Scale Representation Learning for Protein Fitness Prediction
- Zuobai Zhang
- Pascal Notin
- et al.
- 2024
- NeurIPS 2024
A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques
- Megh Thakkar
- Quentin Fournier
- et al.
- 2024
- ACL 2024
Larimar: Large Language Models with Episodic Memory Control
- 2024
- ICML 2024
The Impact of Positional Encoding on Length Generalization in Transformers
- Amirhossein Kazemnejad
- Inkit Padhi
- et al.
- 2023
- NeurIPS 2023
Efficient Equivariant Transfer Learning from Pretrained Models
- Sourya Basu
- Pulkit Katdare
- et al.
- 2023
- NeurIPS 2023
Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction
- Zuobai Zhang
- Minghao Xu
- et al.
- 2023
- NeurIPS 2023
Accelerating Material Design with the Generative Toolkit for Scientific Discovery (GT4SD)
- Matteo Manica
- Joris Cadow
- et al.
- 2022
- ACS Fall 2022