Now, this is something outstanding!😀
Paper-Title: Learning 3D Human Dynamics from Video
#UCB #CVPR_2019
Link to the paper: https://arxiv.org/pdf/1812.01601.pdf
Link to the Github: https://github.com/akanazawa/human_dynamics
Link to the Project page: https://akanazawa.github.io/human_dynamics/

TL;DR: They propose an end-to-end model that learns a model of 3D human dynamics that can 1) obtain smooth 3D prediction from video and 2) hallucinate 3D dynamics on single images at test time.

Here is a list of accepted papers and scheduled presentations.

https://docs.google.com/spreadsheets/u/1/d/1RU2y-iuzwtAR_hn4V9yz1qpZSiElm3iaCpUoDJ-vfvQ/htmlview?sle=true#

Foundations of Machine Learning - A Great Book on Machine Learning

By Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar

MIT Press, Second Edition, 2018

Dr Mehryar Mohri is a Professor of Computer Science and Mathematics at Courant Institute of Mathematical Sciences, New York University

"This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms."

Online Edition:

https://mitpress.ublish.com/ereader/7093/?preview#page/Cover

Deep learning and the Schrödinger equation

By Mills et al.: https://arxiv.org/abs/1702.01361

#ArtificialInteligence #Science #DeepLearning #MachineLearning #Physics #MontrealAI

Translatotron is the first end-to-end model that can directly translate speech from one language into speech in another language. It is also able to retain the source speaker’s voice in the translated speech.


https://ai.googleblog.com/2019/05/introducing-translatotron-end-to-end.html

Meta-Learning with Differentiable Convex Optimization #CVPR2019 Oral

Few-shot learning SoTA on miniImageNet, tieredImageNet, CIFAR-FS, and FC100

Github
https://github.com/kjunelee/MetaOptNet

ArXiv

https://arxiv.org/abs/1904.03758

Neural-Symbolic Computing: An Effective Methodology for Principled Integration of Machine Learning and Reasoning

Garcez et al.: https://arxiv.org/abs/1905.06088

#ArtificialIntelligence #DeepLearning #MachineLearning

On Variational Bounds of Mutual Information
Poole et al.: https://arxiv.org/abs/1905.06922
#ArtificialIntelligence #DeepLearning #MachineLearning

BERT Rediscovers the Classical NLP Pipeline

Tenney et al.: https://arxiv.org/abs/1905.05950

#artificialintelligence #bert #machinelearning #nlp

Does the brain represent words? An evaluation of brain decoding studies of language under... (link: https://arxiv.org/abs/1806.00591) arxiv.org/abs/1806.00591

Number-State Preserving Tensor Networks as Classifiers for Supervised Learning
Glen Evenbly: https://arxiv.org/abs/1905.06352
#QuantumPhysics #DeepLearning #MachineLearning

Deep Compressed Sensing
Wu et al.: https://arxiv.org/pdf/1905.06723.pdf
#deeplearning #generativeadversarialnetworks #technology

Video on self supervised learning of speech representations

By Mirco Ravanelli: https://youtu.be/1zjUmY8L5TU

#deeplearning #selfsupervisedlearning #unsupervisedlearning

Using Deep Learning and TensorFlow Object Detection API for Corrosion Detection and Localization

https://blog.floydhub.com/localize-and-detect-corrosion-with-tensorflow-object-detection-api/

Discrete Flows: Invertible Generative Models of Discrete Data
Tran et al.: https://openreview.net/forum?id=rJlo4UIt_E
#ArtificialIntelligence #DeepLearning #GenerativeModels

Giovani in azione: Mirco Ravanelli – Di Astrid Panizza
12/05/2019
Sulla strada dei cervelli in fuga: dal Trentino al Canada per ricerche sull’intelligenza artificiale
https://www.ladigetto.it/rubriche/giovani_in_azione/87204-giovani-in-azione%3A-mirco-ravanelli-%E2%80%93-di-astrid-panizza.html

ICLR 2019 posters
By Jonathan Binas and Avital Oliver: https://postersession.ai
#deeplearning #ICLR2019 #technology

"Cellular automata as convolutional neural networks"

By William Gilpin: https://arxiv.org/abs/1809.02942

#CellularAutomata #NeuralNetworks #NeuralComputing #EvolutionaryComputing #ComputationalPhysics

Machine Learning in High Energy Physics Community White Paper
Albertsson et al.: https://arxiv.org/abs/1807.02876
#machinelearning #physics #technology

Playing Atari with Six Neurons
Cuccu et al.: https://arxiv.org/abs/1806.01363
#MachineLearning #ArtificialIntelligence #EvolutionaryComputing

Machine Learning in High Energy Physics Community White Paper

Albertsson et al.: https://arxiv.org/abs/1807.02876

#machinelearning #physics #technology