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08/02/2023
Simulation-based inference using surjective sequential neural likelihood estimation
We present Surjective Sequential Neural Likelihood (SSNL) estimation, a ...
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06/27/2023
Adaptive Annealed Importance Sampling with Constant Rate Progress
Annealed Importance Sampling (AIS) synthesizes weighted samples from an ...
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06/02/2023
PassGPT: Password Modeling and (Guided) Generation with Large Language Models
Large language models (LLMs) successfully model natural language from va...
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03/15/2023
Forecasting Particle Accelerator Interruptions Using Logistic LASSO Regression
Unforeseen particle accelerator interruptions, also known as interlocks,...
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02/20/2023
An evaluation of deep learning models for predicting water depth evolution in urban floods
In this technical report we compare different deep learning models for p...
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11/29/2022
Design Space Exploration and Explanation via Conditional Variational Autoencoders in Meta-model-based Conceptual Design of Pedestrian Bridges
For conceptual design, engineers rely on conventional iterative (often m...
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10/18/2022
Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis
Artificial intelligence (AI) is revolutionizing many areas of our lives,...
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09/27/2022
Optimization of Annealed Importance Sampling Hyperparameters
Annealed Importance Sampling (AIS) is a popular algorithm used to estima...
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07/10/2022
Facilitated machine learning for image-based fruit quality assessment in developing countries
Automated image classification is a common task for supervised machine l...
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06/17/2022
OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image Processing
Optoacoustic (OA) imaging is based on excitation of biological tissues w...
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05/23/2022
What You See is What You Classify: Black Box Attributions
An important step towards explaining deep image classifiers lies in the ...
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02/12/2022
TATTOOED: A Robust Deep Neural Network Watermarking Scheme based on Spread-Spectrum Channel Coding
The proliferation of deep learning applications in several areas has led...
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01/28/2022
Learning Summary Statistics for Bayesian Inference with Autoencoders
For stochastic models with intractable likelihood functions, approximate...
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01/24/2022
Deep Reinforcement Learning for Random Access in Machine-Type Communication
Random access (RA) schemes are a topic of high interest in machine-type ...
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01/21/2022
FedComm: Federated Learning as a Medium for Covert Communication
Proposed as a solution to mitigate the privacy implications related to t...
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09/27/2021
Probabilistic modeling of lake surface water temperature using a Bayesian spatio-temporal graph convolutional neural network
Accurate lake temperature estimation is essential for numerous problems ...
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09/24/2021
A data acquisition setup for data driven acoustic design
In this paper, we present a novel interdisciplinary approach to study th...
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08/23/2021
Regularizing Transformers With Deep Probabilistic Layers
Language models (LM) have grown with non-stop in the last decade, from s...
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02/01/2021
A Novel Approach for Classification and Forecasting of Time Series in Particle Accelerators
The beam interruptions (interlocks) of particle accelerators, despite be...
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06/04/2020
Robust Sampling in Deep Learning
Deep learning requires regularization mechanisms to reduce overfitting a...
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11/04/2019
Improved BiGAN training with marginal likelihood equalization
We propose a novel training procedure for improving the performance of g...
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10/15/2019
Probabilistic Time of Arrival Localization
In this paper, we take a new approach for time of arrival geo-localizati...
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10/02/2019
Probabilistic MIMO Symbol Detection with Expectation Consistency Approximate Inference
In this paper we explore low-complexity probabilistic algorithms for sof...
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04/29/2019
Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies
The recent adoption of Electronic Health Records (EHRs) by health care p...
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01/28/2019
Out-of-Sample Testing for GANs
We propose a new method to evaluate GANs, namely EvalGAN. EvalGAN relies...
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10/18/2018
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation
New communication standards need to deal with machine-to-machine communi...
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06/29/2018
Sparse Three-parameter Restricted Indian Buffet Process for Understanding International Trade
This paper presents a Bayesian nonparametric latent feature model specia...
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09/01/2017
PassGAN: A Deep Learning Approach for Password Guessing
State-of-the-art password guessing tools, such as HashCat and John the R...
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05/19/2017
Accelerated Inference for Latent Variable Models
Inference of latent feature models in the Bayesian nonparametric setting...
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02/24/2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
Deep Learning has recently become hugely popular in machine learning, pr...
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10/31/2016
Complex-Valued Kernel Methods for Regression
Usually, complex-valued RKHS are presented as an straightforward applica...
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12/17/2014
Deep Learning for Multi-label Classification
In multi-label classification, the main focus has been to develop ways o...
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07/18/2014
Bayesian Nonparametric Crowdsourcing
Crowdsourcing has been proven to be an effective and efficient tool to a...
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01/29/2014
Bayesian nonparametric comorbidity analysis of psychiatric disorders
The analysis of comorbidity is an open and complex research field in the...
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03/12/2013