activity
20182021
most citedDeep Reasoning Networks: Thinking Fast and Slow

11 citations · 17 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20214 cited

Automating Crystal-Structure Phase Mapping: Combining Deep Learning with Constraint Reasoning

Di Chen, Yiwei Bai, Sebastian Ament +7

Crystal-structure phase mapping is a core, long-standing challenge in materials science that requires identifying crystal structures, or mixtures thereof, in synthesized materials.…

cond-mat.mtrl-sci2020

Optical Identification of Materials Transformations in Oxide Thin Films

Duncan R. Sutherland, Aine Boyer Connolly, Maximilian Amsler +9

Recent advances in high-throughput experimentation for combinatorial studies have accelerated the discovery and analysis of materials across a wide range of compositions and synthe…

cs.LG201911 cited

Deep Reasoning Networks: Thinking Fast and Slow

Di Chen, Yiwei Bai, Wenting Zhao +3

We introduce Deep Reasoning Networks (DRNets), an end-to-end framework that combines deep learning with reasoning for solving complex tasks, typically in an unsupervised or weakly-…

stat.ML20192 cited

Exponentially-Modified Gaussian Mixture Model: Applications in Spectroscopy

Sebastian Ament, John Gregoire, Carla Gomes

We propose a novel exponentially-modified Gaussian (EMG) mixture residual model. The EMG mixture is well suited to model residuals that are contaminated by a distribution with posi…

cs.CV2018

End-to-End Refinement Guided by Pre-trained Prototypical Classifier

Junwen Bai, Zihang Lai, Runzhe Yang +3

Many real-world tasks involve identifying patterns from data satisfying background or prior knowledge. In domains like materials discovery, due to the flaws and biases in raw exper…