Yale University

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Since its founding in 1701, Yale University has been dedicated to expanding and sharing knowledge, inspiring innovation, and preserving cultural and scientific information for future generations.

Benchmark and Best Practices for Biomedical Knowledge Graph Embeddings

Much of biomedical and healthcare data is encoded in discrete, symbolic ...
06/24/2020 ∙ by David Chang, et al. ∙ 51 ∙ share

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CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases

We present CoSQL, a corpus for building cross-domain, general-purpose da...
09/11/2019 ∙ by Tao Yu, et al. ∙ 39 ∙ share

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Using wavelets to analyze similarities in image datasets

Deep learning image classifiers usually rely on huge training sets and t...
02/24/2020 ∙ by Roozbeh Yousefzadeh, et al. ∙ 30 ∙ share

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Spatio-Temporal Segmentation in 3D Echocardiographic Sequences using Fractional Brownian Motion

An important aspect for an improved cardiac functional analysis is the a...
12/21/2019 ∙ by Omar S. Al-Kadi, et al. ∙ 26 ∙ share

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DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior

MRI with multiple protocols is commonly used for diagnosis, but it suffe...
01/11/2020 ∙ by Bo Zhou, et al. ∙ 24 ∙ share

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Permutation invariant networks to learn Wasserstein metrics

Understanding the space of probability measures on a metric space equipp...
10/12/2020 ∙ by Arijit Sehanobish, et al. ∙ 21 ∙ share

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Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study

Pulmonary Embolism (PE) is a life-threatening disorder associated with h...
05/29/2020 ∙ by Luyao Shi, et al. ∙ 20 ∙ share

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Learning Potentials of Quantum Systems using Deep Neural Networks

Machine Learning has wide applications in a broad range of subjects, inc...
06/23/2020 ∙ by Arijit Sehanobish, et al. ∙ 20 ∙ share

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KLT Picker: Particle Picking Using Data-Driven Optimal Templates

Particle picking is currently a critical step in the cryo-EM single part...
12/12/2019 ∙ by Amitay Eldar, et al. ∙ 16 ∙ share

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A Sketching Method for Finding the Closest Point on a Convex Hull

We develop a sketching algorithm to find the point on the convex hull of...
02/21/2021 ∙ by Roozbeh Yousefzadeh, et al. ∙ 15 ∙ share

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TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

It is increasingly common to encounter data from dynamic processes captu...
02/09/2020 ∙ by Alexander Tong, et al. ∙ 14 ∙ share

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Domain Adaptation without Source Data

Domain adaptation assumes that samples from source and target domains ar...
07/03/2020 ∙ by Youngeun Kim, et al. ∙ 14 ∙ share

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Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets

Deep learning models extract, before a final classification layer, featu...
06/17/2020 ∙ by Roozbeh Yousefzadeh, et al. ∙ 11 ∙ share

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A Spectral Regularizer for Unsupervised Disentanglement

Generative models that learn to associate variations in the output along...
12/04/2018 ∙ by Aditya Ramesh, et al. ∙ 10 ∙ share

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The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization

Despite remarkable success, deep neural networks are sensitive to human-...
02/25/2020 ∙ by Yifei Min, et al. ∙ 10 ∙ share

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LOCA: LOcal Conformal Autoencoder for standardized data coordinates

We propose a deep-learning based method for obtaining standardized data ...
04/15/2020 ∙ by Erez Peterfreund, et al. ∙ 10 ∙ share

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Submodular Maximization Through Barrier Functions

In this paper, we introduce a novel technique for constrained submodular...
02/10/2020 ∙ by Ashwinkumar Badanidiyuru, et al. ∙ 9 ∙ share

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Improving Text-to-SQL Evaluation Methodology

To be informative, an evaluation must measure how well systems generaliz...
06/23/2018 ∙ by Catherine Finegan-Dollak, et al. ∙ 8 ∙ share

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TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts

Scientific documents rely on both mathematics and text to communicate id...
02/16/2019 ∙ by Michihiro Yasunaga, et al. ∙ 8 ∙ share

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Auditing and Debugging Deep Learning Models via Decision Boundaries: Individual-level and Group-level Analysis

Deep learning models have been criticized for their lack of easy interpr...
01/03/2020 ∙ by Roozbeh Yousefzadeh, et al. ∙ 8 ∙ share

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Let the Data Choose its Features: Differentiable Unsupervised Feature Selection

Scientific observations often consist of a large number of variables (fe...
07/09/2020 ∙ by Ofir Lindenbaum, et al. ∙ 7 ∙ share

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Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation

Reliable motion estimation and strain analysis using 3D+time echocardiog...
07/12/2018 ∙ by Allen Lu, et al. ∙ 6 ∙ share

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Black Box Submodular Maximization: Discrete and Continuous Settings

In this paper, we consider the problem of black box continuous submodula...
01/28/2019 ∙ by Lin Chen, et al. ∙ 6 ∙ share

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Visualizing the PHATE of Neural Networks

Understanding why and how certain neural networks outperform others is k...
08/07/2019 ∙ by Scott Gigante, et al. ∙ 6 ∙ share

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Activation Density driven Energy-Efficient Pruning in Training

The process of neural network pruning with suitable fine-tuning and retr...
02/07/2020 ∙ by Timothy Foldy-Porto, et al. ∙ 6 ∙ share

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Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

Spiking Neural Networks (SNNs) operate with asynchronous discrete events...
05/04/2020 ∙ by Nitin Rathi, et al. ∙ 6 ∙ share

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Beyond Imitation: Generative and Variational Choreography via Machine Learning

Our team of dance artists, physicists, and machine learning researchers ...
07/11/2019 ∙ by Mariel Pettee, et al. ∙ 4 ∙ share

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Surfing: Iterative optimization over incrementally trained deep networks

We investigate a sequential optimization procedure to minimize the empir...
07/19/2019 ∙ by Ganlin Song, et al. ∙ 3 ∙ share

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Fair quantile regression

Quantile regression is a tool for learning conditional distributions. In...
07/19/2019 ∙ by Dana Yang, et al. ∙ 3 ∙ share

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Coarse Graining of Data via Inhomogeneous Diffusion Condensation

Big data often has emergent structure that exists at multiple levels of ...
07/10/2019 ∙ by Nathan Brugnone, et al. ∙ 2 ∙ share

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Neural Embedding for Physical Manipulations

In common real-world robotic operations, action and state spaces can be ...
07/13/2019 ∙ by Lingzhi Zhang, et al. ∙ 2 ∙ share

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Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation

A deep learning model trained on some labeled data from a certain source...
07/31/2019 ∙ by Junlin Yang, et al. ∙ 2 ∙ share

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Doubly-Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise

A fundamental step in many data-analysis techniques is the construction ...
05/31/2020 ∙ by Boris Landa, et al. ∙ 2 ∙ share

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DANTE: Deep Affinity Network for Clustering Conversational Interactants

We propose a data-driven approach to visually detect conversational grou...
07/24/2019 ∙ by Mason Swofford, et al. ∙ 1 ∙ share

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GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing

We present GraPPa, an effective pre-training approach for table semantic...
09/29/2020 ∙ by Tao Yu, et al. ∙ 1 ∙ share

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Feature Selection Facilitates Learning Mixtures of Discrete Product Distributions

Feature selection can facilitate the learning of mixtures of discrete ra...
11/25/2017 ∙ by Vincent Zhao, et al. ∙ 0 ∙ share

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Manifold learning with bi-stochastic kernels

In this paper we answer the following question: what is the infinitesima...
11/17/2017 ∙ by Ronald R. Coifman, et al. ∙ 0 ∙ share

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Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science

If we pick n random points uniformly in [0,1]^d and connect each point t...
11/13/2017 ∙ by George C. Linderman, et al. ∙ 0 ∙ share

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Multilayer tensor factorization with applications to recommender systems

Recommender systems have been widely adopted by electronic commerce and ...
11/05/2017 ∙ by Xuan Bi, et al. ∙ 0 ∙ share

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Theoretical and Computational Guarantees of Mean Field Variational Inference for Community Detection

The mean field variational Bayes method is becoming increasingly popular...
10/30/2017 ∙ by Anderson Y. Zhang, et al. ∙ 0 ∙ share

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Minimax Estimation of Bandable Precision Matrices

The inverse covariance matrix provides considerable insight for understa...
10/19/2017 ∙ by Addison Hu, et al. ∙ 0 ∙ share

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Weakly Submodular Maximization Beyond Cardinality Constraints: Does Randomization Help Greedy?

Submodular functions are a broad class of set functions, which naturally...
07/13/2017 ∙ by Lin Chen, et al. ∙ 0 ∙ share

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Data-Driven Tree Transforms and Metrics

We consider the analysis of high dimensional data given in the form of a...
08/18/2017 ∙ by Gal Mishne, et al. ∙ 0 ∙ share

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Mahalanonbis Distance Informed by Clustering

A fundamental question in data analysis, machine learning and signal pro...
08/13/2017 ∙ by Almog Lahav, et al. ∙ 0 ∙ share

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Common Variable Learning and Invariant Representation Learning using Siamese Neural Networks

We consider the statistical problem of learning common source of variabi...
12/29/2015 ∙ by Uri Shaham, et al. ∙ 0 ∙ share

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Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization

We propose a general framework for increasing local stability of Artific...
11/17/2015 ∙ by Uri Shaham, et al. ∙ 0 ∙ share

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Clustering with t-SNE, provably

t-distributed Stochastic Neighborhood Embedding (t-SNE), a clustering an...
06/08/2017 ∙ by George C. Linderman, et al. ∙ 0 ∙ share

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The Geometry of Nodal Sets and Outlier Detection

Let (M,g) be a compact manifold and let -Δϕ_k = λ_k ϕ_k be the sequence ...
06/05/2017 ∙ by Xiuyuan Cheng, et al. ∙ 0 ∙ share

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CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks

Simulation is a key component of physics analysis in particle physics an...
05/05/2017 ∙ by Michela Paganini, et al. ∙ 0 ∙ share

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Estimating the coefficients of a mixture of two linear regressions by expectation maximization

We give convergence guarantees for estimating the coefficients of a symm...
04/26/2017 ∙ by Jason M. Klusowski, et al. ∙ 0 ∙ share

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