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06/07/2023
Adversarial Sample Detection Through Neural Network Transport Dynamics
We propose a detector of adversarial samples that is based on the view o...
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05/26/2023
Stability of implicit neural networks for long-term forecasting in dynamical systems
Forecasting physical signals in long time range is among the most challe...
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02/22/2023
Learning from Multiple Sources for Data-to-Text and Text-to-Data
Data-to-text (D2T) and text-to-data (T2D) are dual tasks that convert st...
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12/15/2022
AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions
Surrogate models are necessary to optimize meaningful quantities in phys...
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11/15/2022
HMOE: Hypernetwork-based Mixture of Experts for Domain Generalization
Due to the domain shift, machine learning systems typically fail to gene...
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10/03/2022
Module-wise Training of Residual Networks via the Minimizing Movement Scheme
Greedy layer-wise or module-wise training of neural networks is compelli...
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06/29/2022
An extensible Benchmarking Graph-Mesh dataset for studying Steady-State Incompressible Navier-Stokes Equations
Recent progress in Geometric Deep Learning (GDL) has shown its potential...
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05/19/2022
Diverse Weight Averaging for Out-of-Distribution Generalization
Standard neural networks struggle to generalize under distribution shift...
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05/06/2022
PTFlash: A deep learning framework for isothermal two-phase equilibrium calculations
Phase equilibrium calculations are an essential part of numerical simula...
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02/01/2022
Generalizing to New Physical Systems via Context-Informed Dynamics Model
Data-driven approaches to modeling physical systems fail to generalize t...
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09/24/2021
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction
State-of-the-art NLP models can adopt shallow heuristics that limit thei...
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09/16/2021
Unsupervised domain adaptation with non-stochastic missing data
We consider unsupervised domain adaptation (UDA) for classification prob...
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07/21/2021
Differentiable Feature Selection, a Reparameterization Approach
We consider the task of feature selection for reconstruction which consi...
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06/10/2021
A Neural Tangent Kernel Perspective of GANs
Theoretical analyses for Generative Adversarial Networks (GANs) generall...
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06/08/2021
LEADS: Learning Dynamical Systems that Generalize Across Environments
When modeling dynamical systems from real-world data samples, the distri...
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04/15/2021
Data-QuestEval: A Referenceless Metric for Data to Text Semantic Evaluation
In this paper, we explore how QuestEval, which is a Text-vs-Text metric,...
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03/23/2021
SAFEval: Summarization Asks for Fact-based Evaluation
Summarization evaluation remains an open research problem: current metri...
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02/04/2021
Controlling Hallucinations at Word Level in Data-to-Text Generation
Data-to-Text Generation (DTG) is a subfield of Natural Language Generati...
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11/24/2020
Stochastic sparse adversarial attacks
Adversarial attacks of neural network classifiers (NNC) and the use of r...
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11/13/2020
Transductive Zero-Shot Learning using Cross-Modal CycleGAN
In Computer Vision, Zero-Shot Learning (ZSL) aims at classifying unseen ...
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10/21/2020
PARENTing via Model-Agnostic Reinforcement Learning to Correct Pathological Behaviors in Data-to-Text Generation
In language generation models conditioned by structured data, the classi...
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10/09/2020
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Forecasting complex dynamical phenomena in settings where only partial k...
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09/22/2020
Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!
Despite efforts to distinguish three different evaluation setups (Bekoul...
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09/17/2020
A Principle of Least Action for the Training of Neural Networks
Neural networks have been achieving high generalization performance on m...
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08/04/2020
PDE-Driven Spatiotemporal Disentanglement
A recent line of work in the machine learning community addresses the pr...
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02/25/2020
BERT Can See Out of the Box: On the Cross-modal Transferability of Text Representations
Pre-trained language models such as BERT have recently contributed to si...
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02/21/2020
Stochastic Latent Residual Video Prediction
Designing video prediction models that account for the inherent uncertai...
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02/07/2020
Incorporating Visual Semantics into Sentence Representations within a Grounded Space
Language grounding is an active field aiming at enriching textual repres...
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01/22/2020
Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization
Contextualized embeddings use unsupervised language model pretraining to...
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12/20/2019
A Hierarchical Model for Data-to-Text Generation
Transcribing structured data into natural language descriptions has emer...
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12/18/2019
Unsupervised Adversarial Image Inpainting
We consider inpainting in an unsupervised setting where there is neither...
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06/04/2019
Optimal Unsupervised Domain Translation
Domain Translation is the problem of finding a meaningful correspondence...
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05/30/2019
Regression with Conditional GAN
In recent years, impressive progress has been made in the design of impl...
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04/26/2019
Copy mechanism and tailored training for character-based data-to-text generation
In the last few years, many different methods have been focusing on usin...
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04/24/2019
Context-Aware Zero-Shot Learning for Object Recognition
Zero-Shot Learning (ZSL) aims at classifying unlabeled objects by levera...
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02/26/2019
Learning Dynamical Systems from Partial Observations
We consider the problem of forecasting complex, nonlinear space-time pro...
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04/23/2018
Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery
We introduce a dynamical spatio-temporal model formalized as a recurrent...
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12/20/2017
A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm
We consider the problem of learning a high-dimensional but low-rank matr...
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11/21/2017
Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge
We consider the use of Deep Learning methods for modeling complex phenom...
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11/09/2017
Learning Multi-Modal Word Representation Grounded in Visual Context
Representing the semantics of words is a long-standing problem for the n...
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08/25/2015
OCReP: An Optimally Conditioned Regularization for Pseudoinversion Based Neural Training
In this paper we consider the training of single hidden layer neural net...
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12/17/2014
Extended Recommendation Framework: Generating the Text of a User Review as a Personalized Summary
We propose to augment rating based recommender systems by providing the ...
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12/20/2013
Sequentially Generated Instance-Dependent Image Representations for Classification
In this paper, we investigate a new framework for image classification t...
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04/11/2012
Probabilistic Latent Tensor Factorization Model for Link Pattern Prediction in Multi-relational Networks
This paper aims at the problem of link pattern prediction in collections...
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04/11/2012
Modeling Relational Data via Latent Factor Blockmodel
In this paper we address the problem of modeling relational data, which ...
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02/29/2012
Fast Reinforcement Learning with Large Action Sets using Error-Correcting Output Codes for MDP Factorization
The use of Reinforcement Learning in real-world scenarios is strongly li...
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08/29/2011
Datum-Wise Classification: A Sequential Approach to Sparsity
We propose a novel classification technique whose aim is to select an ap...
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07/07/2011