Full Stack Deep Learning
Tobin et al.: https://course.fullstackdeeplearning.com
#ArtificialIntelligence #DeepLearning #MachineLearning

Deriving Differential Target Propagation from Iterating Approximate Inverses
Yoshua Bengio : https://arxiv.org/abs/2007.15139
#ArtificialIntelligence #DeepLearning #MachineLearning

Analyses of Deep Learning (STATS 385)
Stanford University, Fall 2019 : https://stats385.github.io/lecture_videos
#ArtificialIntelligence #DeepLearning #MachineLearning

List of Open-Source RL Algorithms
By Sergey Kolesnikov, https://docs.google.com/spreadsheets/d/1EeFPd-XIQ3mq_9snTlAZSsFY7Hbnmd7P5bbT8LPuMn0/edit#gid=0
#DeepLearning #MachineLearning #ReinforcementLearning

"Papers with Code": https://paperswithcode.com
#DeepLearning #MachineLearning #NeuralNetworks

Papers with Code partners with arXiv
Robert Stojnic : https://medium.com/paperswithcode/papers-with-code-partners-with-arxiv-ecc362883167

@ArtificialIntelligenceArticles
#MachineLearning #arXiv #Code

Enzyme, a compiler plug-in for importing foreign code into systems like TensorFlow & PyTorch without having to rewrite it. v/@MIT_CSAIL

Paper: https://bit.ly/EnzymePDF

More: https://bit.ly/EnzymeML

#ML #MachineLearning #PyTorch #TensorFlowJS #NeurIPS #tensorflow #AI

Deep learning-enabled medical computer vision

#deeplearning #machinelearning #artificialintelligence #computervision #healthcare #medicalimaging #radiologists #radiology
https://www.nature.com/articles/s41746-020-00376-2

Learning Mesh-Based Simulation with Graph Networks

Pfaff et al.: https://arxiv.org/abs/2010.03409

#MachineLearning #ComputationalEngineering #GraphNetworks

ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision

Kim et al.: https://arxiv.org/abs/2102.03334

#ArtificialIntelligence #DeepLearning #MachineLearning

2021- Courses List of Machine Learning, Deep Learning, and Computer Vision from a top school.
CS224W: Machine Learning with Graphs - Stanford / Winter 2021
https://youtube.com/playlist?list=PLuv1FSpHurUemjLiP4L1x9k6Z9D8rNbYW
Full Stack Deep Learning - Spring 2021 - UC Berkeley
https://youtube.com/playlist?list=PLuv1FSpHurUc2nlabZjCLLe8EQa9fOoa9
Berkeley CS182/282 Deep Learnings - 2021
https://youtube.com/playlist?list=PLuv1FSpHurUevSXe_k0S7Onh6ruL-_NNh\
Introduction to Deep Learning (I2DL) - Technical University of Munich
https://youtube.com/playlist?list=PLuv1FSpHurUdmk7v06MDyIx0SDxTrIoqk
3D Computer Vision - National University of Singapore - 2021
https://youtube.com/playlist?list=PLuv1FSpHurUflLnJF6hgi0FkeNG1zSFCZ
CV3DST - Computer Vision 3: Detection, Segmentation and Tracking
https://youtube.com/playlist?list=PLuv1FSpHurUd08wNo1FMd3eCUZXm8qexe
ADL4CV - Advanced Deep Learning for Computer Vision
https://youtube.com/playlist?list=PLuv1FSpHurUcQi2CwFIVQelSFCzxphJqz
#MachineLearning #artificialintelligence #deeplearning #computervision #MontrealAI

CS224W: Machine Learning with Graphs
Stanford / Winter 2021 [slides] pdf
https://web.stanford.edu/class/cs224w/
#machinelearning #graphs

Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization

Teney et al.: https://arxiv.org/abs/2105.05612

#MachineLearning #DeepLearning #ArtificialIntelligence

Physics-based Deep Learning

Thuerey et al.: https://arxiv.org/abs/2109.05237

#MachineLearning #DeepLearning #Physics

YOLOP: You Only Look Once for Panoptic Driving Perception

Wu et al.: https://arxiv.org/abs/2108.11250

#ArtificialIntelligence #DeepLearning #MachineLearning

2021 DeepMind x UCL Reinforcement Learning Lecture Series
Taught by DeepMind researchers, this series was created in collaboration with University College London (UCL) to offer students a comprehensive introduction to modern reinforcement learning.
Playlist
https://youtube.com/playlist?list=PLki3HkfgNEsKiZXMoYlR-14r1t_MAS7M8
https://youtu.be/_DpLWBG_nvk
#MachineLearning #artificialintelligence #deeplearning #computervision #MontrealAI