Peer-reviewed scientific journal publishing research on machine learning, AI methods, and their applications across science and engineering.
AMIFound, a single model, outperformed 38 baselines at restoring degraded medical images across seven modalities, according to its authors. The downstream results are what make a shared restoration step ahead of clinical AI plausible.
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Sungwoo Lee and colleagues argue that embodied agents should carry an internal environment and let signals from it shape learning and choice. The journal's own editors say the demonstration is still to come.
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GOLLuM fits a language model and a Gaussian process under a single probabilistic objective, so the model learns from being confidently wrong. Its authors report matching classical Bayesian optimisation on over 40 per cent fewer experiments.
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The core ask is architectural: split the state vector into internal and external variables, and give the internal ones their own dynamics. The formalization sits behind a $39.95 paywall.
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A framework called MAP encodes 694,246 mechanistic links over 187,089 drugs, then reports up to 12.3% better zero-shot response prediction. Per drug, that graph averages under four edges.
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A paper published on nature.com argues voxel grids have become the wrong substrate for fast-accumulating instrument data. The cost claim it rests on is the one nobody quantified.
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Cambridge researchers split melody, harmony, rhythm and dynamics into separate model inputs, then identified 20 pianists from 84 hours of recordings. The code and a web app are public.
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