random-matrix-learning / slidesLinks
LaTeX source code for the slides
☆23Updated 3 years ago
Alternatives and similar repositories for slides
Users that are interested in slides are comparing it to the libraries listed below
Sorting:
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆26Updated 4 years ago
- Investigate the speed of adaptation of structural causal models☆15Updated 4 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- PyTorch implementation for "Probabilistic Circuits for Variational Inference in Discrete Graphical Models", NeurIPS 2020☆17Updated 3 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- Nonparametric Score Estimators, ICML 2020☆36Updated 3 years ago
- Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"☆22Updated 2 years ago
- Code for our ICLR Trustworthy ML 2020 workshop paper "Improved Image Wasserstein Attacks and Defenses"☆14Updated 5 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆36Updated 4 years ago
- Optimal Transport for Dummies - Code, slides and article☆32Updated 8 years ago
- ☆30Updated 2 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ☆51Updated 10 months ago
- Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…☆26Updated 10 years ago
- Random feature latent variable models in Python☆22Updated last year
- Official repository for the paper "Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules" (…☆22Updated 2 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Machine Learning Function Approximation: This code implements the fully-connected Deep Neural Network (DNN) architectures considered in t…☆18Updated 4 years ago
- ☆10Updated 3 years ago
- A pytorch version of hamiltonian monte carlo☆14Updated 5 years ago
- A lightweight, multithreaded Python package for sketching, column selection, leverage scores and related computations.☆19Updated 3 weeks ago
- Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)☆22Updated 2 years ago
- Wasserstein regularization for sparse multi-task regression☆15Updated 4 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆13Updated 5 years ago
- code for "Semi-Discrete Normalizing Flows through Differentiable Tessellation"☆26Updated 2 years ago
- Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561☆25Updated 4 years ago
- Automatic Integration for Neural Spatio-Temporal Point Process models (AI-STPP) is a new paradigm for exact, efficient, non-parametric inf…☆24Updated 7 months ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆21Updated 3 years ago