10.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Harvard UniversityUS735 papers
- Massachusetts Institute of TechnologyUS455 papers
- University of OxfordGB379 papers
- University of ChicagoUS368 papers
- University of MichiganUS356 papers
- Lawrence Berkeley National LaboratoryUS354 papers
- The Ohio State UniversityUS350 papers
- Yale UniversityUS348 papers
- University of PittsburghUS317 papers
- Argonne National LaboratoryUS316 papers
- University College LondonGB312 papers
- University of PisaIT310 papers
166 papers · 1 filter
Recursive Formula for Labeled Graph Enumeration
Ravi Goyal, Victor De Gruttola
This manuscript presents a general recursive formula to estimate the size of fibers associated with algebraic maps from graphs to summary statistics of importance for social networ…
Free Energy of the Quantum Sherrington-Kirkpatrick Spin-Glass Model with Transverse Field
Arka Adhikari, Christian Brennecke
We consider the quantum Sherrington-Kirkpatrick (SK) spin-glass model with transverse field and provide a formula for its free energy in the thermodynamic limit, valid for all inve…
ODE-based Deep Network for MRI Reconstruction
Ali Pour Yazdanpanah, Onur Afacan, Simon K. Warfield
Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. The data-driven methods base…
Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Mechanical Ventilation
Kexin Huang, Abhishek Singh, Sitong Chen +4
Clinical notes contain rich data, which is unexploited in predictive modeling compared to structured data. In this work, we developed a new text representation Clinical XLNet for c…
3D Deep Learning Enables Fast Imaging of Spines through Scattering Media by Temporal Focusing Microscopy
Zhun Wei, Josiah R. Boivin, Yi Xue +4
Today the gold standard for in vivo imaging through scattering tissue is the point-scanning two-photon microscope (PSTPM). Especially in neuroscience, PSTPM is widely used for deep…
Electrically controlled emission from triplet charged excitons in atomically thin heterostructures
Andrew Y. Joe, Luis A. Jauregui, Kateryna Pistunova +15
Excitons are composite bosons that can feature spin singlet and triplet states. In usual semiconductors, without an additional spin-flip mechanism, triplet excitons are extremely i…
RTN: Reparameterized Ternary Network
Yuhang Li, Xin Dong, Sai Qian Zhang +3
To deploy deep neural networks on resource-limited devices, quantization has been widely explored. In this work, we study the extremely low-bit networks which have tremendous speed…
SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads
Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj +3
In recent years, there has been tremendous advances in hardware acceleration of deep neural networks. However, most of the research has focused on optimizing accelerator microarchi…
Tropical Geometry and Piecewise-Linear Approximation of Curves and Surfaces on Weighted Lattices
Petros Maragos, Emmanouil Theodosis
Tropical Geometry and Mathematical Morphology share the same max-plus and min-plus semiring arithmetic and matrix algebra. In this chapter we summarize some of their main ideas and…
"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning
Mark Sendak, Madeleine Elish, Michael Gao +6
Machine learning technologies are increasingly developed for use in healthcare. While research communities have focused on creating state-of-the-art models, there has been less foc…
Variable Selection with Rigorous Uncertainty Quantification using Deep Bayesian Neural Networks: Posterior Concentration and Bernstein-von Mises Phenomenon
Jeremiah Zhe Liu
This work develops rigorous theoretical basis for the fact that deep Bayesian neural network (BNN) is an effective tool for high-dimensional variable selection with rigorous uncert…
Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach
Yingying Li, Yujie Tang, Runyu Zhang +1
This paper considers a distributed reinforcement learning problem for decentralized linear quadratic control with partial state observations and local costs. We propose a Zero-Orde…
Electromagnetic signals from the decay of free neutrons in the first hours of neutron star mergers
Ore Gottlieb, Abraham Loeb
The first hours following a neutron star merger are considered to provide several UV/optical/NIR signals: -decay emission from free neutrons, radioactive decay of shocked heavy…
Training Distributed Deep Recurrent Neural Networks with Mixed Precision on GPU Clusters
Alexey Svyatkovskiy, Julian Kates-Harbeck, William Tang
In this paper, we evaluate training of deep recurrent neural networks with half-precision floats. We implement a distributed, data-parallel, synchronous training algorithm by integ…
Predicting skull lesions after clinical transcranial MRI-guided focused ultrasound with acoustic and thermal simulations
Nathan McDannold, P. Jason White, Rees Cosgrove
Transcranial MRI-guided focused ultrasound (TcMRgFUS) thermal ablation is a noninvasive functional neurosurgery technique. Previous reports have shown that bone marrow damage in th…
Mortality for circulatory and respiratory causes associated with influenza circulation in Russia during the 2013/14 through the 2018/19 seasons
Edward Goldstein
Background: Information on influenza-associated mortality in Russia is limited. Methods: Using previously developed methodology (Goldstein et al., Epidemiology 2012), we regressed…
Transmission System Resilience Enhancement with Extended Steady-state Security Region in Consideration of Uncertain Topology Changes
Chong Wang, Feng Wu, Ping Ju +3
The increasing extreme weather events poses unprecedented challenges on power system operation because of their uncertain and sequential impacts on power systems. This paper propos…
Deep neuroethology of a virtual rodent
Josh Merel, Diego Aldarondo, Jesse Marshall +3
Parallel developments in neuroscience and deep learning have led to mutually productive exchanges, pushing our understanding of real and artificial neural networks in sensory and c…
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning
Sanket Shah, Arunesh Sinha, Pradeep Varakantham +2
Large-scale screening for potential threats with limited resources and capacity for screening is a problem of interest at airports, seaports, and other ports of entry. Adversaries…
Ask2Me VarHarmonizer: A Python-Based Tool to Harmonize Variants from Cancer Genetic Testing Reports and Map them to the ClinVar Database
Yuxi Liu, Kanhua Yin, Basanta Lamichhane +18
PURPOSE: The popularity of germline genetic panel testing has led to a vast accumulation of variant-level data. Variant names are not always consistent across laboratories and not…
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations
Himabindu Lakkaraju, Osbert Bastani
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniq…
Semi-Supervised Natural Language Approach for Fine-Grained Classification of Medical Reports
Neil Deshmukh, Selin Gumustop, Romane Gauriau +6
Although machine learning has become a powerful tool to augment doctors in clinical analysis, the immense amount of labeled data that is necessary to train supervised learning appr…
A Hierarchy of Graph Neural Networks Based on Learnable Local Features
Michael Lingzhi Li, Meng Dong, Jiawei Zhou +1
Graph neural networks (GNNs) are a powerful tool to learn representations on graphs by iteratively aggregating features from node neighbourhoods. Many variant models have been prop…
Towards the Use of Neural Networks for Influenza Prediction at Multiple Spatial Resolutions
Emily L. Aiken, Andre T. Nguyen, Mauricio Santillana
We introduce the use of a Gated Recurrent Unit (GRU) for influenza prediction at the state- and city-level in the US, and experiment with the inclusion of real-time flu-related Int…