Our work presents an efficient rare event simulation methodology for black box autonomy using Importance Sampling.
The preprint paper can be accessed in Deep-PrAE arXiv
The examples illustrated in the paper can be accessed here.
Lazy, a tool for running things in idle time Mostly used to stop CUDA ML model training from making my desktop unusable. Simply monitors keyboard/mous
- Please pay attention to the version of SC2 you are using for your experiments. - Performance is *not* always comparable between versions. - The re
Explaining in Style: Official TensorFlow Colab Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang, Yossi Gandelsman,
Bean Machine Overview Bean Machine is a probabilistic programming language for inference over statistical models written in the Python language using
Py2CUDA Convert python code to CUDA. Usage To convert a python file say named py_file.py to CUDA, run python generate_cuda.py --file py_file.py --arch
CycleGAN-VC3-PyTorch 中文说明 | English This code is a PyTorch implementation for paper: CycleGAN-VC3: Examining and Improving CycleGAN-VCs for Mel-spectr
Table of Content Introduction Getting Started Datasets Installation Experiments Training & Testing Pretrained models Texture fine-tuning Demo Toward R
An adaptive hierarchical energy management strategy This project contains the source code of an adaptive hierarchical EMS combining heuristic equivale
Code associated with the paper "Tensor decomposition of higher-order correlations by nonlinear Hebbian learning," Ocker & Buice, Neurips 2021. "plot_f
pyStoNED pyStoNED is a Python package that provides functions for estimating multivariate convex regression, convex quantile regression, convex expect
Binary Stochastic Neurons in PyTorch http://r2rt.com/binary-stochastic-neurons-in-tensorflow.html https://github.com/pytorch/examples/tree/master/mnis
Custom Object Tracking Introduction This repo provides function call to track multi-objects in videos with a given trained object detection model and
Introduction to Deep Learning course resources https://www.coursera.org/learn/intro-to-deep-learning Running on Google Colab (tested for all weeks) Go
Prompt-BERT: Prompt makes BERT Better at Sentence Embeddings Results on STS Tasks Model STS12 STS13 STS14 STS15 STS16 STSb SICK-R Avg. unsup-prompt-be
Pomodouroboros Most pomodoro trackers assume you're going to start them. But time and tide wait for no one - the great pomodoro of the cosmos is cold
Variable-Length-Piano-Infilling The official implementation of Variable-Length Piano Infilling (VLI). (paper: Variable-Length Music Score Infilling vi
Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds This repository is a PyTorch implementation for paper: Uns
NeuralSymbolicRegressionThatScales Pytorch implementation and pretrained models for the paper "Neural Symbolic Regression That Scales", presented at I
AKGNN The source code for Adaptive Kernel Graph Neural Network at AAAI2022. Please cite our paper if you think our work is helpful to you: @inproceedi
Generalized Out-of-Distribution Detection: A Survey 1. Overview This repository is with our survey paper: Title: Generalized Out-of-Distribution Detec
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