A Probabilistic Framework for Modular Continual Learning
- Lazar Valkov
- Akash Srivastava
- et al.
- 2024
- ICLR 2024
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14 results for Akash Srivastava
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations
- Rumen Dangovski
- Li Jing
- et al.
- 2022
- ICLR 2022
Targeted Neural Dynamical Modeling
- Cole Hurwitz
- Akash Srivastava
- et al.
- 2021
- NeurIPS 2021
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
- Kai Xu
- Akash Srivastava
- et al.
- 2021
- NeurIPS 2021
Curiosity-driven Red-teaming for Large Language Models
- Zhang-wei Hong
- Idan Shenfeld
- et al.
- 2024
- ICLR 2024
Analyzing Generalization of Neural Networks through Loss Path Kernels
- Yilan Chen
- Wei Huang
- et al.
- 2023
- NeurIPS 2023
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
- Zhang-wei Hong
- Aviral Kumar
- et al.
- 2023
- NeurIPS 2023
Towards robust and generalizable representations of extracellular data using contrastive learning
- Ankit Vishnubhotla
- Charlotte Loh
- et al.
- 2023
- NeurIPS 2023
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
- Giorgio Giannone
- Akash Srivastava
- et al.
- 2023
- NeurIPS 2023
Generative Ratio Matching Networks
- Akash Srivastava
- Kai Xu
- et al.
- 2020
- ICLR 2020