Researchers from Nanjing University and Carnegie Mellon University have introduced an AI approach that improves how machines learn from past data—a process known as offline reinforcement learning.

With the emergence of huge amounts of heterogeneous multi-modal data, including images, videos, texts/languages, audios, and multi-sensor data, deep learning-based methods have shown promising ...

Researchers from Tohoku University and the Massachusetts Institute of Technology (MIT) have unveiled a new AI tool for high-quality optical spectra with the same accuracy as quantum simulations, but ...

We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...

Alembic Technologies has raised $145 million in Series B and growth funding at a valuation 15 times higher than its previous round, betting that the next competitive advantage in artificial ...

Using MALDI-TOF mass spectrometry for tracking of minimal residual disease in peripheral blood from patients with multiple myeloma. This is an ASCO Meeting Abstract from the 2019 ASCO Annual Meeting I ...