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Showing 1–10 of 10 results
Advanced filters: Author: Yoshua Bengio Clear advanced filters

  • This Perspective explores causal machine learning in single-cell genomics, addressing challenges such as generalization, interpretability and cell dynamics, while highlighting advances and the potential to uncover new insights into cellular mechanisms.

    • Alejandro Tejada-Lapuerta
    • Paul Bertin
    • Fabian J. Theis
    Reviews
    Nature Genetics
    Volume: 57, P: 797-808

  • Artificial intelligence can speed up research into new photovoltaic, battery and carbon-capture materials, argue Edward Sargent, Alán Aspuru-Guzikand colleagues.

    • Phil De Luna
    • Jennifer Wei
    • Edward Sargent
    Comments & Opinion
    Nature
    Volume: 552, P: 23-27

  • Theories of consciousness have a long and controversial history. One well-known proposal — integrated information theory — has recently been labeled as ‘pseudoscience’, which has caused a heated open debate. Here we discuss the case and argue that the theory is indeed unscientific because its core claims are untestable even in principle.

    • Derek H. Arnold
    • Mark G. Baxter
    • Joel S. Snyder
    Comments & Opinion
    Nature Neuroscience
    Volume: 28, P: 689-693

  • One of the ambitions of computational neuroscience is that we will continue to make improvements in the field of artificial intelligence that will be informed by advances in our understanding of how the brains of various species evolved to process information. To that end, here the authors propose an expanded version of the Turing test that involves embodied sensorimotor interactions with the world as a new framework for accelerating progress in artificial intelligence.

    • Anthony Zador
    • Sean Escola
    • Doris Tsao
    ReviewsOpen Access
    Nature Communications
    Volume: 14, P: 1-7

    • Yann LeCun
    • Yoshua Bengio
    • Geoffrey Hinton
    Reviews
    Nature
    Volume: 521, P: 436-444

  • The advances in artificial intelligence over the past decade are examined, with a discussion on how artificial intelligence systems can aid the scientific process and the central issues that remain despite advances.

    • Hanchen Wang
    • Tianfan Fu
    • Marinka Zitnik
    Reviews
    Nature
    Volume: 620, P: 47-60

  • Critical Assessment of Computational Hit-finding Experiments (CACHE) is a public benchmarking project to compare and improve computational small-molecule hit-finding approaches through cycles of prediction, compound synthesis and experimental testing. By that, CACHE will enable a more efficient and effective approach to hit identification and drug discovery.

    • Suzanne Ackloo
    • Rima Al-awar
    • Timothy M. Willson
    Reviews
    Nature Reviews Chemistry
    Volume: 6, P: 287-295

  • A deep network is best understood in terms of components used to design it—objective functions, architecture and learning rules—rather than unit-by-unit computation. Richards et al. argue that this inspires fruitful approaches to systems neuroscience.

    • Blake A. Richards
    • Timothy P. Lillicrap
    • Konrad P. Kording
    Reviews
    Nature Neuroscience
    Volume: 22, P: 1761-1770