lfochamon / csl
csl: PyTorch-based Constrained Learning
☆12Updated 2 years ago
Alternatives and similar repositories for csl:
Users that are interested in csl are comparing it to the libraries listed below
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- LipSDP - Lipschitz Estimation for Neural Networks☆66Updated 3 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆21Updated 2 years ago
- Mixed integer programming for computing lipschitz constants of ReLU Networks☆16Updated 2 years ago
- ☆67Updated 5 months ago
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- ☆17Updated last year
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ☆10Updated 3 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Post-processing for fair classification☆13Updated 3 weeks ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆62Updated 3 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 2 years ago
- ☆58Updated 2 years ago
- ☆16Updated 7 months ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated last year
- Meta-learning Gaussian process (GP) priors via PAC-Bayes bounds☆25Updated last year
- Influence Estimation for Gradient-Boosted Decision Trees☆27Updated 11 months ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆20Updated last year
- Bayesian active learning with EPIG data acquisition☆31Updated 3 weeks ago
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 3 years ago
- An Investigation of Why Overparameterization Exacerbates Spurious Correlations☆31Updated 4 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 4 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year