JeanKossaifi / caltech-tutorial
Material for my Caltech tutorial on deep learning and tensor methods
☆70Updated 6 years ago
Alternatives and similar repositories for caltech-tutorial:
Users that are interested in caltech-tutorial are comparing it to the libraries listed below
- Normalizing Flows in Jax☆107Updated 4 years ago
- ☆28Updated 5 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- Autoregressive Energy Machines☆77Updated 2 years ago
- ☆59Updated 6 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆48Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆184Updated last year
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Implementation and demonstration of backdrop in pytorch. Code and demonstration of GP dataset generator.☆68Updated 6 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- A differentiation API for PyTorch☆30Updated 4 years ago
- Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)☆42Updated 5 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago
- ☆26Updated 6 years ago
- Code for "Efficient optimization of loops and limits with randomized telescoping sums"☆27Updated 5 years ago
- ☆64Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Understanding normalizing flows☆131Updated 5 years ago
- PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.☆99Updated 3 years ago
- ☆30Updated 2 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆105Updated 7 years ago
- TensorFlow implementation of (Momentum) Stochastic Variance-Adapted Gradient.☆44Updated 6 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆44Updated 6 years ago
- TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials☆31Updated 6 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 2 weeks ago
- Stochastic Deep Networks☆17Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 5 years ago