OanaMariaCamburu / CanITrustTheExplainer
☆18Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for CanITrustTheExplainer
- A pytorch implementation for the LSTM experiments in the paper: Why Gradient Clipping Accelerates Training: A Theoretical Justification f…☆44Updated 4 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…☆20Updated last year
- Interpolation between Residual and Non-Residual Networks, ICML 2020. https://arxiv.org/abs/2006.05749☆26Updated 4 years ago
- CVPR 2019 paper "Disentangling Adversarial Robustness and Generalization".☆14Updated 5 years ago
- Label shift experiments☆15Updated 3 years ago
- An Empirical Study of Invariant Risk Minimization☆28Updated 4 years ago
- code for the ICML paper "SelectiveNet - A Deep Neural Network with an Integrated Reject Option"☆45Updated 5 years ago
- ☆65Updated 3 months ago
- ☆42Updated 4 years ago
- ☆29Updated 3 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- code for the paper in NeurIPS 2019☆40Updated last year
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Code for "Generative causal explanations of black-box classifiers"☆33Updated 3 years ago
- Implementation of IMSAT algorithm using Pytorch☆14Updated 6 years ago
- ☆29Updated 6 years ago
- Source code for paper Choromanska et al. -- Beyond Backprop: Online Alternating Minimization with Auxiliary Variables -- http://proceedin…☆24Updated 5 years ago
- Supercharging Imbalanced Data Learning WithCausal Representation Transfer☆12Updated 2 years ago
- ☆40Updated 4 years ago
- Code for experiments in 'Primal Dual Formulation For Deep Learning With Constraints'☆22Updated 5 years ago
- A simple algorithm to identify and correct for label shift.☆21Updated 6 years ago
- PyTorch implementation of Proximal Gradient Algorithms a la Parikh and Boyd (2014). Useful for Auto-Sizing (Murray and Chiang 2015, Murra…☆40Updated 4 years ago
- SGD and Ordered SGD codes for deep learning, SVM, and logistic regression☆34Updated 4 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated last year
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 4 years ago
- ☆30Updated 6 years ago
- ☆16Updated 2 years ago
- A regularized self-labeling approach to improve the generalization and robustness of fine-tuned models☆27Updated 2 years ago
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆27Updated 3 years ago
- Tensorflow code for "Hierarchical Decompositional Mixtures of Variational Autoencoders" (ICML'19)☆12Updated 4 years ago