Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)
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Updated
Apr 14, 2022 - Python
Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)
Official implementation of the paper "You Only Need Adversarial Supervision for Semantic Image Synthesis" (ICLR 2021)
Source code for Fathony, Sahu, Willmott, & Kolter, "Multiplicative Filter Networks", ICLR 2021.
Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and features" (NeurIPS 2020)
Code accompanying Coling2020 publication on data augmentation for named entity recognition
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization
Code base for physics-based photorealistic rendering within the scope of Bosch BCAI AMIRA probject
Blackbox optimization algorithms with a common interface, along with useful helpers like parallel optimization loops, analysis and visualization scripts.
Tensorflow implementation of Meta Adversarial Training for Adversarial Patch Attacks on Tiny ImageNet.
Resources related to ACL 2020 paper "The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain"
A toolbox to explore synchronous layerwise-parallel deep neural networks.
Companion code for the self-supervised anomaly detection algorithm proposed in the paper "Detecting Anomalies within Time Series using Local Neural Transformations" by Tim Schneider et al.
Resources related to EMNLP 2021 paper "FAME: Feature-Based Adversarial Meta-Embeddings for Robust Input Representations"
This is the companion code for the method reported in the paper "Learning game-theoretic models of multiagent trajectories using implicit layers" published at AAAI 2021
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