scottgigante / m-phate
Multislice PHATE for tensor embeddings
☆59Updated 3 years ago
Alternatives and similar repositories for m-phate:
Users that are interested in m-phate are comparing it to the libraries listed below
- Loss Landscapes of Regularized Linear Autoencoders☆144Updated 2 years ago
- Codebase for Learning Invariances in Neural Networks☆93Updated 2 years ago
- Graduate topics course on learning discrete latent structure.☆67Updated 6 years ago
- Repo for open sourcing the NAMs.☆25Updated 4 years ago
- ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows☆53Updated 2 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆111Updated 6 years ago
- Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation☆67Updated 2 years ago
- Mixture Density Networks (Bishop, 1994) tutorial in JAX☆58Updated 4 years ago
- Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."☆43Updated 6 years ago
- A Machine Learning workflow for Slurm.☆149Updated 4 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆63Updated 4 years ago
- Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019☆14Updated 8 months ago
- ☆29Updated 4 years ago
- ☆17Updated 6 years ago
- ☆13Updated 6 months ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)☆47Updated 3 years ago
- Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"☆70Updated 8 years ago
- ☆98Updated 3 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆43Updated 3 years ago
- ☆36Updated 2 years ago
- Pytorch optimizers implementing Hilbert Constrained Gradient Descent☆19Updated 5 years ago
- codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"☆50Updated last year
- Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018☆26Updated 6 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- Tools for training explainable models using attribution priors.☆121Updated 3 years ago
- 🧀 Pytorch code for the Fromage optimiser.☆123Updated 7 months ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- Public Codebase for Rethinking Parameter Counting: Effective Dimensionality Revisited☆37Updated 2 years ago