This repository provides classes for
- Efficient construction of neural networks with PyTorch, including multilayer perceptron (MLP), LSTM, CNN, WideResNet, model ensembles, etc.
- Easy manipulation of networks, including addition and removal of layers and neurons, training of networks, simplification of networks, loading and saving models as a dictionary. See tutorial.ipynb for a simple demonstration.
- PyTorch >= 0.4.1
- scikit-learn
- sympy >= 1.3 for symbolic layers
- LAMP: ICLR 2023 spotlight
- LE-PDE: NeurIPS 2022
- AI Physicist: Physical Review E
- GIB: NeurIPS 2020
- Causal learning: ICML 2019 Time Series Workshop, best poster award
- Meta-learning autoencoder