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monthly digest

AIhub monthly digest: May 2022 – RoboCup virtual, neural collapse, and human-AI collaboration

  30 May 2022
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

The AI pretenders

Researchers in Australia have investigated digital assistants and related privacy concerns of users.

New framework for cooperative bots aims to mimic high-performing human teams

Researchers have developed a robotics system for collaborative bots that work independently to achieve a shared goal.

Researching EU regulation around AI

  23 May 2022
A new research project will investigate regulation around AI, and how the EU approaches this issue.

An experimental design perspective on model-based reinforcement learning

  19 May 2022
We propose a simple algorithm that is able to solve a wide variety of control tasks.

Investigating neural collapse in deep classification networks

  18 May 2022
The winners of an outstanding paper award at ICLR 2022 tell us about their work on understanding deep neural networks.

Should I use offline RL or imitation learning?

  17 May 2022
In this blog post, we aim to understand if, when and why offline RL is a better approach for tackling a variety of sequential decision-making problems.

Using deep learning to predict physical interactions of protein complexes

A computational tool developed to predict the structure of protein complexes is providing new insights into the biomolecular mechanisms of their function.

#ICLR2022 invited talk round-up 2: Beyond interpretability

  06 May 2022
In the second of our round-ups of the invited talks at ICLR we focus on the presentation by Been Kim.

Using machine-learning to distinguish antibody targets

  05 May 2022
Researchers have compiled an informative resource for antibody research and enhanced our molecular understanding of antibody responses.

Offline RL made easier: no TD learning, advantage reweighting, or transformers

  03 May 2022
We try to identify the essential elements of offline RL via supervised learning.

#ICLR2022 invited talk round-up 1: AI for science – protein structure prediction

  29 Apr 2022
In this article, we summarise the ICLR invited talk given by Pushmeet Kohli.
monthly digest

AIhub monthly digest: April 2022 – images of AI, data justice, and winning at bridge

  28 Apr 2022
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Using artificial intelligence in health sciences education requires interdisciplinary collaboration and risk assessment

  19 Apr 2022
To better understand advances in AI as a part of the education of health sciences students, researchers conducted a comprehensive literature review and hosted a virtual panel.

Considering the risks of using AI to help grow our food

  14 Apr 2022
Researchers warn that using new AI technologies at scale holds risks that are not being considered.

Developing safe controllers for autonomous systems under uncertainty

and   05 Apr 2022
Winners of a distinguished paper award at AAAI 2022, Thom S. Badings and Nils Jansen write about their work on robust control of autonomous systems.

Developing an AI-powered app to identify invasive bugs

  04 Apr 2022
A team in Australia is using image recognition to help prevent stink bugs from entering the country.

Unsupervised skill discovery with contrastive intrinsic control

  01 Apr 2022
Unsupervised reinforcement learning (RL), where RL agents pre-train with self-supervised rewards, is an emerging paradigm for developing RL agents that are capable of generalization.
monthly digest

AIhub monthly digest: March 2022 – Lanfrica, AI index report, and conferences galore

  29 Mar 2022
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Deep learning: a framework for image analysis in life sciences

  25 Mar 2022
Researchers explore best practices for applying deep learning methods to bioimaging applications.

Assessing generalization of SGD via disagreement

  21 Mar 2022
We demonstrate that a simple procedure can accurately estimate the generalization error with only unlabeled data.

#AAAI2022 invited talks – data-centric AI and robust deep learning

  16 Mar 2022
Hear from Andrew Ng and Marta Kwiatkowska, two of the plenary speakers at the AAAI Conference on Artificial Intelligence.

imodels: leveraging the unreasonable effectiveness of rules

  14 Mar 2022
imodels provides a simple unified interface and implementation for many state-of-the-art interpretable modeling techniques, particularly rule-based methods.

AI can help doctors work faster – but trust is crucial

  11 Mar 2022
If artificial intelligence is to be of help in healthcare, people and machines must be able to work effectively together.

#AAAI2022 invited talk – Cynthia Rudin on interpretable machine learning

  09 Mar 2022
The winner of the AAAI Squirrel AI award talks about using interpretable models for real-world applications, such as power grids and medicine.

Why spectral normalization stabilizes GANs: analysis and improvements

  07 Mar 2022
We investigate the training stability of generative adversarial networks (GANs).

Bart Selman’s presidential address at #AAAI2022 – incomprehensible truths, fragile chains and hidden crystals

  03 Mar 2022
The current AAAI president talks about the state of AI and highlights three examples of AI for the acceleration of scientific discovery.

Hot papers on arXiv from the past month: February 2022

  02 Mar 2022
What’s hot on arXiv? Here are the most tweeted papers that were uploaded onto arXiv during February 2022.
monthly digest

AIhub monthly digest: February 2022 – AAAI 2022 in progress, the life of a dataset, and AI valentines

  28 Feb 2022
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Artificial intelligence and big data to help preserve wildlife

  25 Feb 2022
Research collaborators propose that animal ecologists can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge.

Beach bots, sea ‘raptors’ and marine toolsets mobilised to get rid of marine litter

  18 Feb 2022
Find out about the different EU research projects are concerned with reducing marine litter, including an autonomous litter-picking robot.

The unsupervised reinforcement learning benchmark

  14 Feb 2022
We consider the unsupervised RL problem - how do we learn useful behaviors without supervision and then adapt them to solve downstream tasks quickly?

Improving RL with lookahead: learning off-policy with online planning

  11 Feb 2022
We suggest using a policy that looks ahead using a learned model to find the best action sequence.

Machine learning fine-tunes graphene synthesis

  08 Feb 2022
Rice University lab uses computer models to advance graphene synthesis process.

Sequence modeling solutions for reinforcement learning problems

  03 Feb 2022
We tackle large-scale reinforcement learning problems with the toolbox of sequence modeling.






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