fd17 / SciNet_PyTorch
A PyTorch implementation of the SciNet Paper
☆35Updated 4 years ago
Related projects: ⓘ
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆29Updated 2 years ago
- Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"☆23Updated 4 years ago
- Tensorflow implementation of equation learner☆29Updated 3 years ago
- EQL Function Learning Network☆9Updated 3 years ago
- PyTorch implementation of the EQL network, a neural network for symbolic regression☆38Updated 3 years ago
- Physics-Enhanced Latent Space Variational Autoencoder☆8Updated last year
- predicting equations from raw data with deep learning☆55Updated 5 years ago
- Code for "Machine-Learning Non-Conservative Dynamics for New-Physics Detection" (arXiv: 2106.00026)☆14Updated 3 years ago
- PyGL: statistical field theory in Python. github.com/rajeshrinet/pygl☆23Updated 7 months ago
- Spring 2023 seminar on automated experiment☆23Updated last year
- ☆68Updated 4 years ago
- ☆16Updated 2 years ago
- Notebooks for "A high bias low-variance introduction to Machine Learning for physicists."☆65Updated 4 years ago
- Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"☆69Updated last year
- Deep Bayesian Optimization for Problems with High-Dimensional Structure☆14Updated last year
- [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.☆23Updated 3 months ago
- ☆170Updated last year
- Stiff Neural Ordinary Differential Equations☆30Updated last year
- Convolutional Solvers for Partial Differential Equations☆28Updated 4 years ago
- This project provides Slow Feature Analysis as a scikit-learn-style package.☆33Updated 11 months ago
- Counting the number of conservation laws from trajectory data☆18Updated 3 years ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆141Updated 4 years ago
- Physics informed Bayesian network + autoencoder for matching process / variable / performance in solar cells.☆30Updated 3 years ago
- Equation Learner, a neural network approach to symbolic regression☆68Updated 3 years ago
- mechanics, statistical mechanics, fluid dynamics, thermodynamics, quantum mechanics, electromagnetism☆21Updated 4 years ago
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆16Updated 3 years ago
- Physics-Informed Neural Networks for Solving Multiscale Mode-Resolved Phonon Boltzmann Transport Equation☆17Updated 2 years ago
- Implementation of restricted Boltzmann machines in Tensorflow 2☆25Updated last year
- Code for the paper "Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks" (https://arxiv.org/abs/2206.…☆9Updated 2 years ago
- Code to estimate Renormalized Mutual Information in simple settings☆12Updated 3 years ago