epfml / autoTrain
Open Challenge - Automatic Training for Deep Learning
☆3Updated 2 years ago
Related projects: ⓘ
- ☆61Updated last year
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆67Updated 4 years ago
- 👩 Pytorch and Jax code for the Madam optimiser.☆50Updated 3 years ago
- Computing various norms/measures on over-parametrized neural networks☆48Updated 5 years ago
- ☆26Updated 5 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- Pip-installable differentiable stacks in PyTorch!☆65Updated 3 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆39Updated 5 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆50Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆83Updated 2 years ago
- Implementations of quasi-hyperbolic optimization algorithms.☆100Updated 4 years ago
- Geometric Certifications of Neural Nets☆41Updated last year
- TBA☆75Updated 5 years ago
- A library for evaluating representations.☆76Updated 2 years ago
- Autoregressive Energy Machines☆77Updated last year
- The Singular Values of Convolutional Layers☆71Updated 5 years ago
- Mixture Density Networks (Bishop, 1994) tutorial in JAX☆57Updated 4 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆183Updated last year
- Notes from NeurIPS 2019☆29Updated 4 years ago
- ☆76Updated 4 years ago
- 🧀 Pytorch code for the Fromage optimiser.☆120Updated 2 months ago
- Ἀνατομή is a PyTorch library to analyze representation of neural networks☆61Updated 10 months ago
- Keras implementation of Deep Wasserstein Embeddings☆46Updated 6 years ago
- The Synbols dataset generator is a ServiceNow Research project that was started at Element AI.☆43Updated last year
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- ☆45Updated 4 years ago
- Graduate topics course on learning discrete latent structure.☆66Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆33Updated 4 years ago