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    Should I use offline RL or imitation learning?
    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.
    17 May 2022, by

    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.
    12 May 2022, by

    #ICLR2022 invited talk round-up 2: Beyond interpretability
    In the second of our round-ups of the invited talks at ICLR we focus on the presentation by Been Kim.
    06 May 2022, by

    Using machine-learning to distinguish antibody targets
    Researchers have compiled an informative resource for antibody research and enhanced our molecular understanding of antibody responses.
    05 May 2022, by

    Offline RL made easier: no TD learning, advantage reweighting, or transformers
    We try to identify the essential elements of offline RL via supervised learning.
    03 May 2022, by

    #ICLR2022 invited talk round-up 1: AI for science – protein structure prediction
    In this article, we summarise the ICLR invited talk given by Pushmeet Kohli.
    29 April 2022, by

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    AIhub monthly digest: April 2022 – images of AI, data justice, and winning at bridge
    Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
    28 April 2022, by

    Trainee teachers made sharper assessments about learning difficulties after receiving feedback from AI
    Using AI to help trainee teachers in their assessments of students.
    26 April 2022, by

    Using artificial intelligence in health sciences education requires interdisciplinary collaboration and risk assessment
    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.
    19 April 2022, by

    Considering the risks of using AI to help grow our food
    Researchers warn that using new AI technologies at scale holds risks that are not being considered.
    14 April 2022, by

    Developing safe controllers for autonomous systems under uncertainty
    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.
    05 April 2022, by and

    Developing an AI-powered app to identify invasive bugs
    A team in Australia is using image recognition to help prevent stink bugs from entering the country.
    04 April 2022, by

    Unsupervised skill discovery with contrastive intrinsic control
    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.
    01 April 2022, by

    AIhub monthly digest: March 2022 – Lanfrica, AI index report, and conferences galore
    Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
    29 March 2022, by

    Deep learning: a framework for image analysis in life sciences
    Researchers explore best practices for applying deep learning methods to bioimaging applications.
    25 March 2022, by

    Assessing generalization of SGD via disagreement
    We demonstrate that a simple procedure can accurately estimate the generalization error with only unlabeled data.
    21 March 2022, by

    #AAAI2022 invited talks – data-centric AI and robust deep learning
    Hear from Andrew Ng and Marta Kwiatkowska, two of the plenary speakers at the AAAI Conference on Artificial Intelligence.
    16 March 2022, by

    imodels: leveraging the unreasonable effectiveness of rules
    imodels provides a simple unified interface and implementation for many state-of-the-art interpretable modeling techniques, particularly rule-based methods.
    14 March 2022, by

    AI can help doctors work faster – but trust is crucial
    If artificial intelligence is to be of help in healthcare, people and machines must be able to work effectively together.
    11 March 2022, by

    #AAAI2022 invited talk – Cynthia Rudin on interpretable machine learning
    The winner of the AAAI Squirrel AI award talks about using interpretable models for real-world applications, such as power grids and medicine.
    09 March 2022, by

    Why spectral normalization stabilizes GANs: analysis and improvements
    We investigate the training stability of generative adversarial networks (GANs).
    07 March 2022, by

    Bart Selman’s presidential address at #AAAI2022 – incomprehensible truths, fragile chains and hidden crystals
    The current AAAI president talks about the state of AI and highlights three examples of AI for the acceleration of scientific discovery.
    03 March 2022, by

    Hot papers on arXiv from the past month: February 2022
    What’s hot on arXiv? Here are the most tweeted papers that were uploaded onto arXiv during February 2022.
    02 March 2022, by

    AIhub monthly digest: February 2022 – AAAI 2022 in progress, the life of a dataset, and AI valentines
    Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
    28 February 2022, by

    Artificial intelligence and big data to help preserve wildlife
    Research collaborators propose that animal ecologists can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge.
    25 February 2022, by

    Beach bots, sea ‘raptors’ and marine toolsets mobilised to get rid of marine litter
    Find out about the different EU research projects are concerned with reducing marine litter, including an autonomous litter-picking robot.
    18 February 2022, by

    The unsupervised reinforcement learning benchmark
    We consider the unsupervised RL problem - how do we learn useful behaviors without supervision and then adapt them to solve downstream tasks quickly?
    14 February 2022, by

    Improving RL with lookahead: learning off-policy with online planning
    We suggest using a policy that looks ahead using a learned model to find the best action sequence.
    11 February 2022, by

    Machine learning fine-tunes graphene synthesis
    Rice University lab uses computer models to advance graphene synthesis process.
    08 February 2022, by

    Sequence modeling solutions for reinforcement learning problems
    We tackle large-scale reinforcement learning problems with the toolbox of sequence modeling.
    03 February 2022, by

     
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