jcyang34 / lspin
☆11Updated last year
Alternatives and similar repositories for lspin:
Users that are interested in lspin are comparing it to the libraries listed below
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ☆30Updated 3 years ago
- MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space☆40Updated 3 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆39Updated 4 years ago
- ☆35Updated last year
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- A study on the following problems: what the memorization problem is in meta-learning; why memorization problem happens; and how we can pr…☆21Updated last year
- ☆20Updated 4 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆41Updated last year
- ☆12Updated last year
- ModelDiff: A Framework for Comparing Learning Algorithms☆54Updated last year
- An Empirical Framework for Domain Generalization In Clinical Settings☆29Updated 2 years ago
- ☆43Updated 2 years ago
- Code for "Generative causal explanations of black-box classifiers"☆33Updated 4 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆32Updated last year
- Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".☆27Updated 3 years ago
- Code for "Few-Shot Learning by Dimensionality Reduction in Gradient Space"☆14Updated last year
- Active and Sample-Efficient Model Evaluation☆24Updated 3 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 4 years ago
- ☆19Updated last year
- A benchmark for distribution shift in tabular data☆48Updated 7 months ago
- ☆18Updated 3 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆67Updated 3 years ago
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆65Updated last year
- ☆32Updated 6 years ago
- ☆22Updated 2 years ago
- ☆65Updated 5 months ago
- Anytime Learning At Macroscale☆9Updated 3 years ago