95 citations · 430 across the 31 of their papers we have counts for
17 papers · 1 filter
RotationOut as a Regularization Method for Neural Network
Kai Hu, Barnabas Poczos
In this paper, we propose a novel regularization method, RotationOut, for neural networks. Different from Dropout that handles each neuron/channel independently, RotationOut regard…
End-to-end particle and event identification at the Large Hadron Collider with CMS Open Data
John Alison, Sitong An, Michael Andrews +8
From particle identification to the discovery of the Higgs boson, deep learning algorithms have become an increasingly important tool for data analysis at the Large Hadron Collider…
Better Approximate Inference for Partial Likelihood Models with a Latent Structure
Amrith Setlur, Barnabás Póczós
Temporal Point Processes (TPP) with partial likelihoods involving a latent structure often entail an intractable marginalization, thus making inference hard. We propose a novel app…
Developing Creative AI to Generate Sculptural Objects
Songwei Ge, Austin Dill, Eunsu Kang +4
We explore the intersection of human and machine creativity by generating sculptural objects through machine learning. This research raises questions about both the technical detai…
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
Ksenia Korovina, Sailun Xu, Kirthevasan Kandasamy +4
In applications such as molecule design or drug discovery, it is desirable to have an algorithm which recommends new candidate molecules based on the results of past tests. These m…
A Deep Reinforcement Learning Approach for Global Routing
Haiguang Liao, Wentai Zhang, Xuliang Dong +3
Global routing has been a historically challenging problem in electronic circuit design, where the challenge is to connect a large and arbitrary number of circuit components with w…