🧀 Pytorch code for the Fromage optimiser.
☆129Jul 14, 2024Updated last year
Alternatives and similar repositories for fromage
Users that are interested in fromage are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Jun 12, 2023Updated 3 years ago
- An adaptive training algorithm for residual network☆17Aug 22, 2020Updated 5 years ago
- Code base for SRSGD.☆27Mar 5, 2020Updated 6 years ago
- Discovering Neural Wirings (https://arxiv.org/abs/1906.00586)☆138Mar 5, 2026Updated 3 months ago
- Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)☆12Jan 10, 2023Updated 3 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆105Feb 18, 2020Updated 6 years ago
- Improving Transformation Invariance in Contrastive Representation Learning☆12Mar 13, 2021Updated 5 years ago
- Code accompanying our paper "Finding trainable sparse networks through Neural Tangent Transfer" to be published at ICML-2020.☆13Jun 14, 2020Updated 6 years ago
- LibCP -- A Library for Conformal Prediction☆13Feb 26, 2015Updated 11 years ago
- ☆25May 20, 2020Updated 6 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆58Apr 11, 2021Updated 5 years ago
- EfficientNet, MobileNetV3, MobileNetV2, MixNet, etc in JAX w/ Flax Linen and Objax☆130Jan 4, 2024Updated 2 years ago
- Codebase for Learning Invariances in Neural Networks☆96Oct 7, 2022Updated 3 years ago
- ☆12Dec 20, 2019Updated 6 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- ☆42Oct 2, 2018Updated 7 years ago
- [NeurIPS'20] GradAug: A New Regularization Method for Deep Neural Networks☆93Dec 16, 2020Updated 5 years ago
- ☆133Mar 23, 2021Updated 5 years ago
- Code for NeurIPS 2019 paper: "Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes…☆253Aug 26, 2020Updated 5 years ago
- Distilling Model Failures as Directions in Latent Space☆48Feb 8, 2023Updated 3 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆89Feb 1, 2024Updated 2 years ago
- ☆12Jan 27, 2017Updated 9 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆25Sep 4, 2022Updated 3 years ago
- NeurIPS 2019 Paper Implementation☆12Nov 22, 2022Updated 3 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- An empirical investigation of deep learning theory☆16Oct 3, 2019Updated 6 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆48Sep 19, 2019Updated 6 years ago
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Sep 13, 2020Updated 5 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆48Aug 17, 2021Updated 4 years ago
- ☆64Feb 7, 2024Updated 2 years ago
- Fast and Easy Infinite Neural Networks in Python☆2,385Mar 1, 2024Updated 2 years ago
- ☆14Jun 5, 2020Updated 6 years ago
- Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression☆19Oct 12, 2021Updated 4 years ago
- Learning Robust Dynamics Through Variational Sparse Gating☆20Oct 19, 2022Updated 3 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆68Dec 9, 2020Updated 5 years ago
- Parameter Efficient Transfer Learning with Diff Pruning☆74Feb 3, 2021Updated 5 years ago
- Probabilistic Solution of Differential Equations☆13Jun 19, 2022Updated 3 years ago
- Python library for argument and configuration management☆57Feb 7, 2023Updated 3 years ago
- Loss and accuracy go opposite ways...right?☆94May 14, 2020Updated 6 years ago
- DOOM source port in Eiffel with SDL2☆11Sep 9, 2025Updated 9 months ago
- Convolutional Neural Tangent Kernel☆112Oct 22, 2019Updated 6 years ago