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Collection of notebooks about quantitative finance, with interactive python code.
Generate 3D objects conditioned on text or images
Ripser++: GPU-accelerated computation of Vietoris–Rips persistence barcodes
Python implementation of GLN in different frameworks
Understanding Rare Spurious Correlations in Neural Network
multilabel-learn: Multilabel-Classification Algorithms
All Algorithms implemented in Python
A game theoretic approach to explain the output of any machine learning model.
Geometric Certifications of Neural Nets
RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vacc…
Pytorch Implementation of OpenAI's PixelCNN++
[PYTHON] Search for image using Google Custom Search API and resize & crop afterwards
Implementation of Confidence-Calibrated Adversarial Training (CCAT).
♾️ CML - Continuous Machine Learning | CI/CD for ML
Implementation of the k-means algorithm in PyTorch that works for large datasets
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem [CVPR 2019, oral]
code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018
Contest Proposal and infrastructure for the Unrestricted Adversarial Examples Challenge
Differentiable rendering without approximation.
A Closer Look at Accuracy vs. Robustness
Ingest portfolio and other data from multiple brokerages, and analyze it
A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.
Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019