2 citations · 5 across the 4 of their papers we have counts for
4 papers
Discovery and recovery of crystalline materials with property-conditioned transformers
Cyprien Bone, Matthew Walker, Bradley A. A. Martin +6
Generative models have recently shown great promise for accelerating the design and discovery of new functional materials. Conditional generation enhances this capacity by allowing…
Learning disentangled latent representations facilitates discovery and design of functional materials
Jaehoon Cha, Tingyao Lu, Matthew Walker +1
The discovery of new materials is often constrained by the need for large labelled datasets or expensive simulations. In this study, we explore the use of Disentangling Autoencoder…
The carbon cost of materials discovery: Can machine learning really accelerate the discovery of new photovoltaics?
Matthew Walker, Keith T. Butler
Computational screening has become a powerful complement to experimental efforts in the discovery of high-performance photovoltaic (PV) materials. Most workflows rely on density fu…
Practical Marketplace Optimization at Uber Using Causally-Informed Machine Learning
Bobby Chen, Siyu Chen, Jason Dowlatabadi +15
Budget allocation of marketplace levers, such as incentives for drivers and promotions for riders, has long been a technical and business challenge at Uber; understanding lever bud…