nik-dim / sequelLinks
A Continual Learning Library in PyTorch and JAX
☆14Updated 2 years ago
Alternatives and similar repositories for sequel
Users that are interested in sequel are comparing it to the libraries listed below
Sorting:
- ☆107Updated last year
- Code release for REPAIR: REnormalizing Permuted Activations for Interpolation Repair☆47Updated last year
- Git Re-Basin: Merging Models modulo Permutation Symmetries in PyTorch☆75Updated 2 years ago
- Codebase used in the paper "Foundational Models for Continual Learning: An Empirical Study of Latent Replay".☆30Updated 2 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- Spurious Features Everywhere - Large-Scale Detection of Harmful Spurious Features in ImageNet☆32Updated last year
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆28Updated last year
- IIRC: Incremental Implicitly Refined Classification☆30Updated 2 years ago
- ☆40Updated 2 years ago
- ☆26Updated 3 years ago
- The PackNet Continual Learning Method in Pytorch☆14Updated 3 years ago
- ☆38Updated 7 months ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- ☆45Updated 2 years ago
- Visual Representation Learning Benchmark for Self-Supervised Models☆36Updated last year
- This repository contains the code for our paper "Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguo…☆40Updated 2 years ago
- A simple and efficient baseline for data attribution☆11Updated last year
- MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)☆109Updated 2 years ago
- NEVIS'22: Benchmarking the next generation of never-ending learners☆102Updated 2 years ago
- Codebase for the paper titled "Continual learning with local module selection"☆25Updated 3 years ago
- ☆34Updated last year
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆40Updated last year
- ☆95Updated 2 years ago
- Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?☆40Updated 2 years ago
- CL-Gym: Full-Featured PyTorch Library for Continual Learning☆40Updated last year
- [NeurIPS'22] Official Repository for Characterizing Datapoints via Second-Split Forgetting☆15Updated last year
- Code for the paper "The Journey, Not the Destination: How Data Guides Diffusion Models"☆22Updated last year
- ☆34Updated last week
- This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?☆12Updated 2 years ago