ICLR 2020 Cancelled Over Coronavirus; Virtual Conference Arranged
Organizers announced today that the COVID-19 outbreak and associated travel restrictions have forced the cancellation of the “physical conference” ofContinue Reading
Tag: technology
Augmented Training Scheme Fixes CNN Texture Bias
Researchers proposed a new training scheme that targets this bias by controlling and exposing textural information slowly through the training process.
AutoCompress: SOTA Automatic DNN Pruning for Ultra-High Compression Rates
Researchers proposed an automatic structured pruning framework, AutoCompress, which adopts the 2018 ADMM-based weight pruning algorithm and outperforms previous automatic model compression methods while maintaining high accuracy.
Google DeepMind Releases Structure Predictions for Coronavirus Linked Proteins
DeepMind released the structure predictions for six proteins associated with SARS-CoV-2, the virus that causes COVID-19, using the most up-to-date version of their AlphaFold system.
100M Masks/Day: Automated Production Lines Work Overtime to Stop COVID-19 Spread
Pushed by the coronavirus outbreak, in early March 2020 China’s face mask production hit 110 percent capacity, with daily output exceeding 100 million masks according to state agency statistics.
AI-Based Drug Discovery Pipeline Generates Novel Drug Compounds against Coronavirus
A new study leverages an established AI-based drug discovery pipeline to produce molecular structures as part of the widening fight against the 2019-nCoV outbreak.
Yoshua Bengio and Team Introduce GNN Benchmarking Framework
Researchers propose a flexible GNN benchmarking framework that can also accommodate the needs of researchers to add new datasets and models.
Spotting Generated Images Just Got Much Easier
UC Berkeley and Adobe Research have introduced a “universal” detector that can distinguish real images from generated images regardless of what architectures and/or datasets were used for training.
CookGAN Generates Realistic Meal Images From an Ingredients List
Proposed by researchers from the Rutgers University and Samsung AI Center in the UK, CookGAN uses an attention-based ingredients-image association model to condition a generative neural network tasked with synthesizing meal images.
KaoKore: New Facial Dataset from Japanese Scrolls for ML
The KaoKore dataset includes 5552 RGB image files drawn from the 2018 Collection of Facial Expressions dataset of cropped face images from Japanese artworks.
CVPR 2020 Proceeding as Planned; Record 1470 Papers Accepted
The paper acceptance rate fell to approximately 22 percent from 25 percent in 2019 and 29.6 percent in 2018.
Robot Lovers Rejoice! Fei-Fei Li Stanford Team Crowd-Sources World’s Largest Robot Manipulation Dataset
The crowdsourcing produced 111.25 hours of video from 54 non-expert demonstrators to build “one of the largest, richest, and most diverse robot manipulation datasets ever collected using human creativity and dexterity.”
AI Enables Doctors to Diagnose COVID-19 Infection in Seconds
Fast and accurate diagnosis is critical on the front line, and now an AI-powered diagnostic assessment system is helping Hubei medical teams do just that.
Retrieving Reasoning Paths for Answering Complex Questions
In an attempt to equip the TF-IDF-based retriever with a state-of-the-art neural reading comprehension model, researchers introduced a new graph-based recurrent retrieval approach.
Aerial Visual Search of the Continental USA in 0.1 Seconds
The proposed system is capable of searching the continental United States at 1 -meter pixel resolution, corresponding to approximately 2 billion images, in around 0.1 seconds.
MonoLayout | Bird’s-Eye Layout Estimation from A Single Image
MonoLayout, a practical deep neural architecture that takes just a single image of a road scene as input and outputs an amodal scene layout in bird’s-eye view.
Bengio and Mila Researchers Use GAN Images to Illustrate Impact of Climate Change
In a bid to raise awareness of the threats posed by climate change, the Mila team recently published a paper that uses GANs to generate images of how climate events may impact our environments — with a particular focus on floods.
YOLO Creator Joseph Redmon Stopped CV Research Due to Ethical Concerns
Joseph Redmon, creator of the popular object detection algorithm YOLO, tweeted last week that he had ceased his computer vision research to avoid enabling potential misuse of the tech.
NeurIPS 2020 Changes Review Process; Hinton & Google Brain Unsupervised Model Boosts ImageNet Accuracy 7%; DeepMind Releases New JAX Libraries
Synced Global AI Weekly February 23rd
DeepMind Releases New JAX Libraries for Neural Networks and Reinforcement Learning
DeepMind announced yesterday the release of Haiku and RLax — new JAX libraries designed for neural networks and reinforcement learning respectively.
Introduction to Deep Learning for Graphs and Where It May Be Heading
Researchers from Italy’s University of Pisa present a clear and engaging tutorial on the main concepts and building blocks involved in neural architectures for graphs.
Anime-zing GANILLA for Ghibli Style Image Transfer
Researchers have proposed a novel generator network specialized on the illustrations in children’s books.
Allen Institute’s New ‘Computer Vision Explorer’ Lets Researchers Demo SOTA CV Models
The tool enables researchers to try, compare, and evaluate models to decide which work best on their datasets or for their research purposes.
AAAI 2020 Best Papers; Turing Award Winners See a Turning Point for Deep Learning; MIT Reveals Voting App Vulnerabilities
Synced Global AI Weekly February 16th
‘ClearGrasp’ Helps Robots See and Grasp Transparent Objects
Google teamed up with researchers from Synthesis AI and Columbia University to introduce a deep learning approach called ClearGrasp as a first step to teaching machines how to “see” transparent materials.
Google Brain & CMU Semi-Supervised ‘Noisy Student’ Achieves 88.4% Top-1 Accuracy on ImageNet
Researchers from Google Brain and Carnegie Mellon University have released models trained with a semi-supervised learning method called “Noisy Student” that achieve 88.4 percent top-1 accuracy on ImageNet.
Unsupervised Approach for GAN Interpretability Through Semantic Direction Discovery
Researchers have introduced the first unsupervised learning approach for identifying interpretable semantic directions in the latent space of generative adversarial network (GAN) models.
17 Billion Parameters! Microsoft DeepSpeed Breeds World’s Largest NLP Model
Deep learning models are getting larger and larger to meet the demand for better and better performance. Meanwhile, the timeContinue Reading
Beyond SPADE: Introducing Semantic Region-Adaptive Normalization for Image Synthesis
Researchers introduced semantic region-adaptive normalization (SEAN), a simple but effective building block for conditional Generative Adversarial Networks (cGAN).
Facebook Open-Sources PyTorch3D CV Library
In a bid to simplify 3D deep learning and improve processing performance and efficiency, Facebook recently introduced an open-source framework for 3D computer vision.
Research Roundup: Science & Technology Versus the 2019 Novel Coronavirus
Synced Global AI Weekly February 9th
Battling the Coronavirus: Alibaba and Baidu AI Accelerate Vaccine and Drug R&D
The crucial step now is to develop matching vaccines and drugs to uproot its existence, and China’s big tech companies have stepped up to help.
Batchboost: Regularization for Stabilizing Training With Resistance to Underfitting & Overfitting
Batchboost is a simple technique to accelerate ML model training by adaptively feeding mini-batches with artificial samples which are created by mixing two examples from the previous step – in favor of pairing those that produce the difficult one.
Sing Along! Japanese Researchers Develop Multispeaker Corpus for Singing Voice Synthesis
In an effort to enrich resources for multispeaker singing-voice synthesis, a team of researchers from the University of Tokyo has developed a Japanese multispeaker singing-voice corpus.
Radioactive Data: Facebook AI Knows Where You Got Your Training Dataset
Researchers proposed a “radioactive data” technique for subtly marking images in a dataset to help researchers later determine whether they were used to train a particular model.
Machine Unlearning: Fighting for the Right to Be Forgotten
In a new paper, researchers from the University of Toronto, Vector Institute, and University of Wisconsin-Madison propose SISA training, a new framework that helps models “unlearn” information by reducing number of updates that need to be computed when data points are removed.
Using Rotation, Translation, and Cropping to Boost Generalization in Deep Reinforcement Learning Models
In a new paper, researchers from the New York University and Modl.ai, a company applying machine learning to game developing, suggest that simple spacial processing methods such as rotation, translation and cropping could help increase model generality.
Baidu Open-Sources RNA Prediction Algorithm for 2019 Novel Coronavirus
The tool can significantly accelerate the prediction time of a virus’s RNA secondary structure, affording frontline researchers an opportunity to better understand the virus and develop targeting vaccines in a time of crisis.
Facebook HiPlot ‘Makes Understanding High Dimensional Data Easy’
Facebook’s new HiPlot is a lightweight interactive visualization tool that takes this further, using parallel plots to discover correlations and patterns in such high-dimensional data.
A Look at ‘Escaping From Saddle Points on Riemannian Manifolds’
A new paper from the University of Washington Seattle and the University of California, Berkeley looks at saddle points on Riemannian Manifolds. In this article Synced takes a deep dive into this important research.