NVIDIA Novel vid2vid Framework Synthesizes Realistic World-Consistent Videos
NVIDIA researchers propose a novel vid2vid framework that utilizes all past generated frames during rendering.
Category: Machine Learning & Data Science
Popular Microsoft Chatbot XiaoIce Gains Independence as a New Company Led by Di Li and Harry Shum
Microsoft announced it would spin off its chatbot business XiaoIce, with all associated technologies licensed to a newly formed independent company.
ProtTrans Delivers SOTA Pretrained Language Models for Proteins
Researchers launched the ProtTrans Project, which provides an outstanding model for protein pretraining.
PLATO-2: The State-Of-The-Art Open-Domain Chatbot in Chinese and English
PLATO-2, a open-domain chatbot model, can talk about anything in Chinese and English and engage in deep conversations.
Facebook & CMU Introduce TaBERT for Understanding Tabular Data Queries
TaBERT-powered neural semantic parsers showed performance improvements on the challenging benchmark WikiTableQuestions and demonstrated competitive performance on the text-to-SQL dataset Spider.
Introducing TayPO, a Unifying Framework for Reinforcement Learning
Researchers proposed a Taylor Expansion Policy Optimization (TayPO) framework that combines two leading algorithmic improvement methods.
ICML 2020 Announces Outstanding Paper Awards
The acceptance rate of 21.8 percent is slightly lower than 2019’s 22.6 percent (774 accepted papers from 3,424 submissions).
DeepMind Explores Generalization and Efficiency in Algorithm Design
DeepMind introduced a new approach designed to improve the generalizability and efficiency of algorithms represented by neural networks.
New Google Research Incorporates Societal Context in ML Systems
To promote fairer ML systems, the team introduced a collaborative causal theory formation that incorporates diverse stakeholder perspectives for discovering and considering societal context.
DeepMind Explores Deep RL for Brain and Behaviour Research
DeepMind researchers call attention to another “fundamentally novel” development in AI research — deep reinforcement learning (deep RL) — which they believe also has vital implications for neuroscience and deserves more attention from neuroscientists.
Viral Post Highlights ‘Toxicity Problems’ in the Machine Learning Community
The post highlights perceived peer-review problems, the reproducibility crisis, and ethics and diversity issues.
Grand Theft Auto Scene Context Data Boosts Human Motion Prediction
A team of researchers proposed a novel three-stage learning framework that includes scene context to generate long-term 3D human motion prediction when given a single scene image and 2D pose histories.
Researchers Propose ‘Neuro-Symbolic’ Approach for Generative Art
Researchers propose a neuro-symbolic hybrid approach to address the challenge of creativity in generative art.
ACL 2020 Announces Best Paper & Test-Of-Time Awards
Organizers of the 58th Annual Meeting of the Association for Computational Linguistics (ACL) today announced their Best Paper Awards.
‘Beyond the ConvNet’ -Stanford & MIT Neural Network Learns Physical Graph Representations from Video
Researchers introduce a novel Physical Scene Graphs (PSG) approach designed to obtain a better structured understanding of visual scenes.
Facebook Introduces Integrated Eye & Face Model for 3D Immersion in Remote Communication
The proposed method generalizes well across various degrees of eye openness, different identities, and combinations of eye and lower facial expressions.
ICML 2020 Announces Test of Time Award
Organizers of the 37th International Conference on Machine Learning (ICML) have announced this year’s Test of Time award, which goes to a team from the California Institute of Technology, University of Pennsylvania, Saarland University.
NetHack: Fast & Complex Learning Environment For Testing RL Agent Robustness & Generalization
NLE is a procedurally generated environment for testing the robustness and systematic generalization of RL agents.
Yann LeCun Quits Twitter Amid Acrimonious Exchanges on AI Bias
Turing Award Winner and Facebook Chief AI Scientist Yann LeCun has announced his exit from Twitter after getting involved in a long and often acrimonious dispute regarding racial biases in AI.
Princeton, DeepMind & NYU Research Distills Symbolic Representations of DL Models Using Inductive Biases
A team of researchers from Princeton, DeepMind and New York University have introduced a new method that extracts symbolic representations from deep learning models by introducing strong induction biases.
Deep Graph Contrastive Representation Learning
This paper presents a novel contrastive framework for unsupervised graph representation learning.
Stanford ‘SIRENs’ Apply Periodic Activation Functions to Implicit Neural Representations
The researchers introduce sinusoidal representation networks (SIRENs) as a method for leveraging periodic activation functions for implicit neural representations.
Reimagining the Dog: New DeepMind Models and Tutorial for Physics-Based RL Tasks
DeepMind researchers released several new models and a tutorial for their dm_control software stack for physics-based simulation and reinforcement learning environments using MuJoCo physics.
Fourier Feature Mapping Enables MLPs to Learn High-Frequency Functions in Low-Dimensional Domains
Researchers have proposed the use of Fourier feature mapping with MLPs in order to learn high-frequency functions in low-dimensional problem domains.
Google & DeepMind Researchers Revamp ImageNet
Google Brain in Zürich and DeepMind London researchers believe one of the world’s most popular image databases may need a makeover.
Google Brain’s SimCLRv2 Achieves New SOTA in Semi-Supervised Learning
Following on the February release of its contrastive learning framework SimCLR, the same team of Google Brain researchers guided by Turing Award honouree Dr. Geoffrey Hinton has presented SimCLRv2, an upgraded approach that boosts the SOTA results by 21.6 percent.
Answering Multi-Hop Open-Domain Questions With Graph-Based Recurrent Retrieval
Researchers from the University of Washington, Salesforce Research and Allen Institute for Artificial Intelligence have introduced a graph-based method that retrieves reasoning paths to boost multi-hop open-domain question answering.
From Texts to Kitties: OpenAI’s GPT Language Model Tackles Image Generation
Large transformer-based language models trained on pixel sequences can generate coherent images without the use of labels.
Google Brain Rethinks Pre-training and Self-training
A team of researchers from Google Brain have proposed a rethink of the dominant computer vision paradigm of pre-training.
Local Motion Phases Technique Boosts Basketball Animation Richness and Realism
Researchers have proposed a novel framework that learns fast and dynamic character interactions.
AI Startup Covariant.ai Building ‘Universal AI for Robots’
Covariant last month secured a US$40 million Series B funding round led by Index Ventures to push its total funding to US$67 million.
Dance to the Music! Stick Figures Groove With New ‘seq2seq’ Model & Curriculum Learning
Researchers from Fudan University and Microsoft have proposed a novel seq2seq architecture that generates dance sequences for music clips running a minute or longer.
Facebook and Kaggle Face Backlash After Disqualifying Apparent ‘Deepfake Detection Challenge’ Winner
Facebook and Kaggle are facing an online backlash after the apparent winners of the Deepfake Detection Challenge (DFDC) were disqualified.
Facebook and UC Berkeley Boost CV Performance and Lower Compute Cost With Visual Transformers
A team of researchers from Facebook and UC Berkeley has proposed a new paradigm for computer vision.
Toward Practical Real-World RL: New Criterion & Algorithm Enhance Deployment Efficiency
Researchers from the University of Tokyo and Google Research have proposed a new metric for RL performance and novel BREMEN algorithm designed to manage the costs and risks of new policy deployment.
A Look at Recent Advances in Google Translate
In a recent Google AI team blog post, researchers report on recent efforts and progress in the field of language translation, especially with resource-poor languages.
Uber ATG Open-Sources Neuropod DL Inference Engine
Neuropod, an open-source library that provides a uniform interface for running deep learning (DL) models from multiple frameworks in C++ and Python.
DeepMind Introduces ‘EATS’ – An Adversarial, End-to-End Approach to TTS
DeepMind researchers have developed EATS, a generative model trained adversarially in an end-to-end manner that achieves performance comparable to SOTA models.
DeepFaceDrawing Generates Photorealistic Portraits from Freehand Sketches
A team of researchers from the Chinese Academy of Sciences and the City University of Hong Kong has introduced a local-to-global approach that can generate lifelike human portraits from relatively rudimentary sketches.
Unsupervised Image Classification Approach Outperforms SOTA Methods by ‘Huge Margins’
Researchers from Katholieke Universiteit Leuven in Belgium and ETH Zürich in a recent paper propose a two-step approach for unsupervised classification.