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Featured Researchers

Wei Chen
199 publications
Max Welling
141 publications
Qiang Liu
116 publications
Anima Anandkumar
115 publications
Zhe Wang
94 publications
Yi Li
88 publications
Long Chen
85 publications
Yang Feng
79 publications
Hao Tang
70 publications
Deva Ramanan
65 publications
Cheng Zhang
60 publications

Sherpa: Robust Hyperparameter Optimization for Machine Learning

Sherpa is a hyperparameter optimization library for machine learning mod...
05/08/2020 ∙ by Lars Hertel, et al. ∙ 111 ∙ share

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Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity

There is a lack of scalable quantitative measures of reactivity for func...
03/24/2021 ∙ by Mohammadamin Tavakoli, et al. ∙ 70 ∙ share

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A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting

We study epidemic forecasting on real-world health data by a graph-struc...
02/13/2019 ∙ by Zhijian Li, et al. ∙ 26 ∙ share

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Probabilistic Kernel Support Vector Machines

We propose a probabilistic enhancement of standard kernel Support Vecto...
04/14/2019 ∙ by Yongxin Chen, et al. ∙ 24 ∙ share

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Learning from Learning Machines: Optimisation, Rules, and Social Norms

There is an analogy between machine learning systems and economic entiti...
12/29/2019 ∙ by Travis LaCroix, et al. ∙ 24 ∙ share

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Obtaining Faithful Interpretations from Compositional Neural Networks

Neural module networks (NMNs) are a popular approach for modeling compos...
05/02/2020 ∙ by Sanjay Subramanian, et al. ∙ 22 ∙ share

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Extreme Classification via Adversarial Softmax Approximation

Training a classifier over a large number of classes, known as 'extreme ...
02/15/2020 ∙ by Robert Bamler, et al. ∙ 20 ∙ share

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Tightening Bounds for Variational Inference by Revisiting Perturbation Theory

Variational inference has become one of the most widely used methods in ...
09/30/2019 ∙ by Robert Bamler, et al. ∙ 19 ∙ share

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Improving Inference for Neural Image Compression

We consider the problem of lossy image compression with deep latent vari...
06/07/2020 ∙ by Yibo Yang, et al. ∙ 19 ∙ share

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Image Augmentations for GAN Training

Data augmentations have been widely studied to improve the accuracy and ...
06/04/2020 ∙ by Zhengli Zhao, et al. ∙ 18 ∙ share

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SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness

We introduce SPLASH units, a class of learnable activation functions sho...
06/16/2020 ∙ by Mohammadamin Tavakoli, et al. ∙ 17 ∙ share

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Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning

Reinforcement learning algorithms can show strong variation in performan...
07/29/2020 ∙ by Lars Hertel, et al. ∙ 16 ∙ share

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Neuromodulated Patience for Robot and Self-Driving Vehicle Navigation

Robots and self-driving vehicles face a number of challenges when naviga...
09/14/2019 ∙ by Jinwei Xing, et al. ∙ 13 ∙ share

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Image Reconstruction with Predictive Filter Flow

We propose a simple, interpretable framework for solving a wide range of...
11/28/2018 ∙ by Shu Kong, et al. ∙ 12 ∙ share

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Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation

Leveraging synthetically rendered data offers great potential to improve...
02/27/2020 ∙ by Yunhan Zhao, et al. ∙ 12 ∙ share

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Sparsity Meets Robustness: Channel Pruning for the Feynman-Kac Formalism Principled Robust Deep Neural Nets

Deep neural nets (DNNs) compression is crucial for adaptation to mobile ...
03/02/2020 ∙ by Thu Dinh, et al. ∙ 12 ∙ share

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Multi-View Collaborative Network Embedding

Real-world networks often exist with multiple views, where each view des...
05/17/2020 ∙ by Sezin Kircali Ata, et al. ∙ 12 ∙ share

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Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis

We present a method for learning "spectrally descriptive" edge weights f...
06/29/2021 ∙ by Cory Braker Scott, et al. ∙ 12 ∙ share

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Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving

In Autonomous Vehicles (AVs), one fundamental pillar is perception, whic...
07/16/2019 ∙ by Yulong Cao, et al. ∙ 11 ∙ share

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Weakly Supervised Lesion Localization With Probabilistic-CAM Pooling

Localizing thoracic diseases on chest X-ray plays a critical role in cli...
05/29/2020 ∙ by Wenwu Ye, et al. ∙ 11 ∙ share

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AnatomyNet: Deep 3D Squeeze-and-excitation U-Nets for fast and fully automated whole-volume anatomical segmentation

Radiation therapy (RT) is a common treatment for head and neck (HaN) can...
08/15/2018 ∙ by Wentao Zhu, et al. ∙ 10 ∙ share

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Explain Your Move: Understanding Agent Actions Using Focused Feature Saliency

As deep reinforcement learning (RL) is applied to more tasks, there is a...
12/23/2019 ∙ by Piyush Gupta, et al. ∙ 10 ∙ share

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Neural Compression and Filtering for Edge-assisted Real-time Object Detection in Challenged Networks

The edge computing paradigm places compute-capable devices - edge server...
07/31/2020 ∙ by Yoshitomo Matsubara, et al. ∙ 10 ∙ share

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Active Bayesian Assessment for Black-Box Classifiers

Recent advances in machine learning have led to increased deployment of ...
02/16/2020 ∙ by Disi Ji, et al. ∙ 9 ∙ share

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Predicting Camera Viewpoint Improves Cross-dataset Generalization for 3D Human Pose Estimation

Monocular estimation of 3d human pose has attracted increased attention ...
04/07/2020 ∙ by Zhe Wang, et al. ∙ 9 ∙ share

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Split Computing for Complex Object Detectors: Challenges and Preliminary Results

Following the trends of mobile and edge computing for DNN models, an int...
07/27/2020 ∙ by Yoshitomo Matsubara, et al. ∙ 8 ∙ share

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Memory capacity of neural networks with threshold and ReLU activations

Overwhelming theoretical and empirical evidence shows that mildly overpa...
01/20/2020 ∙ by Roman Vershynin, et al. ∙ 7 ∙ share

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Tourbillon: a Physically Plausible Neural Architecture

In a physical neural system, backpropagation is faced with a number of o...
07/13/2021 ∙ by Mohammadamin Tavakoli, et al. ∙ 7 ∙ share

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Sparse Representations for Object and Ego-motion Estimation in Dynamic Scenes

Dynamic scenes that contain both object motion and egomotion are a chall...
03/09/2019 ∙ by Hirak J Kashyap, et al. ∙ 6 ∙ share

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Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets

Training activation quantized neural networks involves minimizing a piec...
03/13/2019 ∙ by Penghang Yin, et al. ∙ 6 ∙ share

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Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications

Representing entities and relations in an embedding space is a well-stud...
05/02/2019 ∙ by Pouya Pezeshkpour, et al. ∙ 6 ∙ share

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On Robustness of Lane Detection Models to Physical-World Adversarial Attacks in Autonomous Driving

After the 2017 TuSimple Lane Detection Challenge, its evaluation based o...
07/06/2021 ∙ by Takami Sato, et al. ∙ 6 ∙ share

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Safe-by-Repair: A Convex Optimization Approach for Repairing Unsafe Two-Level Lattice Neural Network Controllers

In this paper, we consider the problem of repairing a data-trained Recti...
04/06/2021 ∙ by Ulices Santa Cruz, et al. ∙ 5 ∙ share

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Bounding the Complexity of Formally Verifying Neural Networks: A Geometric Approach

In this paper, we consider the computational complexity of formally veri...
12/22/2020 ∙ by James Ferlez, et al. ∙ 4 ∙ share

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Curiosity-Driven Multi-Criteria Hindsight Experience Replay

Dealing with sparse rewards is a longstanding challenge in reinforcement...
06/09/2019 ∙ by John B. Lanier, et al. ∙ 3 ∙ share

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Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and Indoor Scene Layouts

We develop new representations and algorithms for three-dimensional (3D)...
06/11/2019 ∙ by Zhile Ren, et al. ∙ 3 ∙ share

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Blended Coarse Gradient Descent for Full Quantization of Deep Neural Networks

Quantized deep neural networks (QDNNs) are attractive due to their much ...
08/15/2018 ∙ by Penghang Yin, et al. ∙ 2 ∙ share

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Neural Multi-Scale Self-Supervised Registration for Echocardiogram Dense Tracking

Echocardiography has become routinely used in the diagnosis of cardiomyo...
06/18/2019 ∙ by Wentao Zhu, et al. ∙ 2 ∙ share

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Affordance Analysis of Virtual and Augmented Reality Mediated Communication

Virtual and augmented reality communication platforms are seen as promis...
04/09/2019 ∙ by Mohammad Keshavarzi, et al. ∙ 1 ∙ share

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PyCARL: A PyNN Interface for Hardware-Software Co-Simulation of Spiking Neural Network

We present PyCARL, a PyNN-based common Python programming interface for ...
03/21/2020 ∙ by Adarsha Balaji, et al. ∙ 1 ∙ share

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Continuous Representation of Molecules Using Graph Variational Autoencoder

In order to continuously represent molecules, we propose a generative mo...
04/17/2020 ∙ by Mohammadamin Tavakoli, et al. ∙ 1 ∙ share

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Test-Time Training for Deformable Multi-Scale Image Registration

Registration is a fundamental task in medical robotics and is often a cr...
03/25/2021 ∙ by Wentao Zhu, et al. ∙ 1 ∙ share

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Counterfactual Explanations Can Be Manipulated

Counterfactual explanations are emerging as an attractive option for pro...
06/04/2021 ∙ by Dylan Slack, et al. ∙ 1 ∙ share

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Universal halting times in optimization and machine learning

The authors present empirical distributions for the halting time (measur...
11/19/2015 ∙ by Levent Sagun, et al. ∙ 0 ∙ share

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DeepLung: 3D Deep Convolutional Nets for Automated Pulmonary Nodule Detection and Classification

In this work, we present a fully automated lung CT cancer diagnosis syst...
09/16/2017 ∙ by Wentao Zhu, et al. ∙ 0 ∙ share

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Square-Contact Representations of Partial 2-Trees and Triconnected Simply-Nested Graphs

A square-contact representation of a planar graph G=(V,E) maps vertices ...
10/01/2017 ∙ by Giordano Da Lozzo, et al. ∙ 0 ∙ share

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Weakly Supervised Action Localization by Sparse Temporal Pooling Network

We propose a weakly supervised temporal action localization algorithm on...
12/14/2017 ∙ by Phuc Nguyen, et al. ∙ 0 ∙ share

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Improving Malware Detection Accuracy by Extracting Icon Information

Detecting PE malware files is now commonly approached using statistical ...
12/10/2017 ∙ by Pedro Silva, et al. ∙ 0 ∙ share

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Adversarial Deep Structured Nets for Mass Segmentation from Mammograms

Mass segmentation provides effective morphological features which are im...
10/24/2017 ∙ by Wentao Zhu, et al. ∙ 0 ∙ share

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Mondrian Processes for Flow Cytometry Analysis

Analysis of flow cytometry data is an essential tool for clinical diagno...
11/21/2017 ∙ by Disi Ji, et al. ∙ 0 ∙ share

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