brando90 / ultimate-anatome
Ἀνατομή is a PyTorch library to analyze representation of neural networks
☆12Updated last year
Alternatives and similar repositories for ultimate-anatome:
Users that are interested in ultimate-anatome are comparing it to the libraries listed below
- Code base for SRSGD.☆28Updated 5 years ago
- ☆35Updated last year
- A pytorch implementation for the LSTM experiments in the paper: Why Gradient Clipping Accelerates Training: A Theoretical Justification f…☆45Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- SGD with large step sizes learns sparse features [ICML 2023]☆32Updated last year
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness☆44Updated 3 years ago
- ☆14Updated 5 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Updated 4 years ago
- CIFAR-5m dataset☆38Updated 4 years ago
- This repo contains the code used for NeurIPS 2019 paper "Asymmetric Valleys: Beyond Sharp and Flat Local Minima".☆14Updated 5 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 3 years ago
- Code for the paper "Semi-Conditional Normalizing Flows for Semi-Supervised Learning"☆10Updated 5 years ago
- ☆36Updated 3 years ago
- The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…☆40Updated 4 years ago
- Python library for argument and configuration management☆54Updated 2 years ago
- Ἀνατομή is a PyTorch library to analyze representation of neural networks☆62Updated last year
- Monotone operator equilibrium networks☆51Updated 4 years ago
- ☆41Updated 2 years ago
- ☆11Updated 2 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks☆10Updated 9 months ago
- ☆15Updated 4 years ago
- ☆66Updated 6 years ago
- Bootstrap Your Own Latent (BYOL) pytorch implementation using DistributedDataParallel.☆28Updated 2 years ago
- Code for the ICML 2021 and ICLR 2022 papers: Skew Orthogonal Convolutions, Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100☆18Updated 3 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- An adaptive training algorithm for residual network☆15Updated 4 years ago
- ☆34Updated 3 years ago