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Latent Variable Models for Neural Activity

Official PyTorch Implementation for Conflict-Averse Gradient Descent (CAGrad)

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image corruptions"

Code for "On Adaptive Attacks to Adversarial Example Defenses"

Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"

Move and resize windows on macOS with keyboard shortcuts and snap areas

Code, data and benchmark from the paper "Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming" (NeurIPS 2019 ML4AD)

Code for the CVPR 2019 article "Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses"

Comparative Study of Deep Learning Software Frameworks

Creating abstract art images with CPPNs

Code for the ICCV 2019 paper "Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation"

i-RevNet Pytorch Code

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

Corruption and Perturbation Robustness (ICLR 2019)

Pretrained bag-of-local-features neural networks

Neural Nearest Neighbors Networks (NIPS*2018)

Adversarially Robust Neural Network on MNIST.

Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling

Lightweight library to build and train neural networks in Theano