Poster session location: Lawson Commons. Join us for a two-day workshop exploring the latest developments in scientific machine learning, where theory, algorithms, and real-world applications converge ...

We propose a dimensionality reducing matrix design based on training data with constraints on its Frobenius norm and number of rows. Our design criteria is aimed at preserving the distances between ...

Artificial intelligence is already a part of everyday life. It helps us answer questions like “Is this email spam?” It identifies friends in online photographs, selects news stories based on our ...

Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...

Data-Driven Model Selection using Weak SINDy with Applications to Spatiotemporal Problems in Biology The task of identifying governing equations to match observed phenomena is crucial to understanding ...

In 1994, MIT professor of applied mathematics Peter Shor developed a groundbreaking quantum computing algorithm capable of factoring numbers (that is, finding the prime numbers for any integer N) ...