epfml / autoTrainLinks
Open Challenge - Automatic Training for Deep Learning
☆4Updated 3 years ago
Alternatives and similar repositories for autoTrain
Users that are interested in autoTrain are comparing it to the libraries listed below
Sorting:
- 👩 Pytorch and Jax code for the Madam optimiser.☆51Updated 4 years ago
- ☆61Updated 2 years ago
- ☆26Updated 6 years ago
- Mixture Density Networks (Bishop, 1994) tutorial in JAX☆60Updated 5 years ago
- Boiler plate code for Torch based ML projects☆10Updated 3 years ago
- Geometric Certifications of Neural Nets☆42Updated 2 years ago
- Code for "Systematic Generalization: What Is Required and Can It Be Learned"☆37Updated 6 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆42Updated 6 years ago
- TBA☆75Updated 6 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 3 months ago
- ☆45Updated 5 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Loss Patterns of Neural Networks☆85Updated 3 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 5 years ago
- The Singular Values of Convolutional Layers☆72Updated 6 years ago
- Pip-installable differentiable stacks in PyTorch!☆65Updated 4 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- [AAAI 2020 Oral] Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution☆38Updated 4 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- 🧀 Pytorch code for the Fromage optimiser.☆124Updated 11 months ago
- Framework-agnostic library for checking array/tensor shapes at runtime.☆46Updated 4 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 5 years ago
- ☆32Updated 6 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆40Updated 5 years ago
- Code for NeurIPS 2019 paper: "Symmetry-Based Disentangled Representation Learning requires Interaction with Environments" by H. Caselles-…☆35Updated 5 years ago
- Autoregressive Energy Machines☆78Updated 2 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- ☆49Updated 4 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆41Updated last year