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Machine Learning

Computer Vision

Artificial Intelligence

Deep Learning for Daily Fire Danger Prediction

Deep Learning Methods for Daily Wildfire Danger Forecasting

Wildfire forecasting is of paramount importance for disaster risk reductionand environmental sustainability.

We approach daily fire danger prediction as a machine learning task, using historical earth observation data from the last decade to predict next-day's fire danger.

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Machine Learning

A Systematic Review of Deep Time Series Prediction Literature

Time Series Prediction using Deep Learning Methods in Healthcare

Recent deep learning methods have shown promising performance for various healthcare prediction tasks by addressing the high-dimensional and temporal challenges of medical data.

Traditional machine learning methods face two main challenges in dealing with healthcare predictive analytics tasks.

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Machine Learning

Methodology

Interpretable Deep Learning for Cognitive Decoding

Challenges for cognitive decoding using deep learning methods

Deep learning (dl)methods are highly promising for cognitive decoding, with their unmatchedability to learn versatile representations of complex data.

Yet, their widespread application in cognitive decoding is hindered by their general lack of interpretability as well as difficulties in applying them to small datasets and in ensuring their reproducibility and robustness.

Machine Learning

Artificial Intelligence

Graphs as Tools to Improve Deep Learning Methods

In recent years, deep neural networks (DNNs) have known an important rise in popularity. However, although they are state-of-the-art in many machine learning challenges, they still suffer from several

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Machine Learning

Artificial Intelligence

Continual Learning with Deep Learning Methods in an Application-Oriented Context

Abstract knowledge is deeply grounded in many computer-based applications. An important research area of Artificial Intelligence (AI) deals with the automatic derivation of knowledge from data. Machin

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Information Retrieval

Computation and Language

Hybrid deep learning methods for phenotype prediction from clinical notes

Identifying patient cohorts from clinical notes in secondary electronic health records is a fundamental task in clinical information management. The patient cohort identification needs to identify the

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Chemical Physics

Quantum Physics

Deep learning methods for the computation of vibrational wavefunctions

In this paper we design and use two Deep Learning models to generate the ground and excited wavefunctions of different Hamiltonians suitable for the study the vibrations of molecular systems. The gene

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Machine Learning

Computer Vision

Image and Video Processing

A review of deep learning methods for MRI reconstruction

Following the success of deep learning in a wide range of applications, neural network-based machine-learning techniques have received significant interest for accelerating magnetic resonance imaging

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Machine Learning

Computer Vision

Image and Video Processing

Artificial Intelligence

A Survey of eXplainable Artificial Intelligence for Medical Diagnosis

Explainable Deep Learning Methods in Medical Diagnosis: A Survey

Deep learning models are hardly adopted in clinical workflows,mainly due to their lack of interpretability.

The black-box-ness of deeplearning models has raised the need for devising strategies to explain the decision process of these models, leading to the creation of the topic of explainable artificial intelligence (xai).

Stats Machine Learning

Theoretical Perspectives on Deep Learning Methods in Inverse Problems

In recent years, there have been significant advances in the use of deep learning methods in inverse problems such as denoising, compressive sensing, inpainting, and super-resolution. While this line

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Artificial Intelligence

Deep Reinforcement Learning for the Hungry Geese Environment

An Exploration of Deep Learning Methods in Hungry Geese

This paper looks at state of the art value based deep reinforcement learning methods and applies it as an exercise to other environments.

Hungry geese is a n-player variation of the popular game snake.

Machine Learning

Computer Vision

Instrumentation and Methods for Astrophysics

Artificial Intelligence

Solar and Stellar Astrophysics

Automatic Detection of Occulted Hard X-ray Flares Using Deep-Learning Methods

We present a concept for a machine-learning classification of hard X-ray (HXR) emissions from solar flares observed by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI), identifying fl

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Machine Learning

Stats Machine Learning

Using Deep Neural Networks to Estimate Causal Effects in the Presence of Unmeasured Confounding Assumptions

Deep Learning Methods for Proximal Inference via Maximum Moment Restriction

We introduce a flexible and scalable method based on a deep neural network to estimate causal effects in the presence of unmeasured confounding using proximal inference.

Our method achieves state of the art performance on two well-established proximalinference benchmarks.

Computer Vision

Deep Learning Methods for Vessel Trajectory Prediction based on Recurrent Neural Networks

Data-driven methods open up unprecedented possibilities for maritime surveillance using Automatic Identification System (AIS) data. In this work, we explore deep learning strategies using historical A

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Machine Learning

Computer Vision

Artificial Intelligence

Efficient Deep Learning Methods for Identification of Defective Casting Products

Quality inspection has become crucial in any large-scale manufacturing industry recently. In order to reduce human error, it has become imperative to use efficient and low computational AI algorithms

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Computer Vision

Image and Video Processing

Deep Learning for Despeckling of Synthetic Aneurysm Radar Images

Deep learning methods for SAR image despeckling: trends and perspectives

Synthetic aperture radar (sar) images are affected by a spatially-correlated and signal-dependent noise called speckle, which is very severe and may hinder image exploitation.

Despeckling is an important task that aims at removing such noise, so as to improve the accuracy of all downstream image processing tasks.

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Machine Learning

Cryptography and Security

Deep Learning Techniques for Network Intrusion Detection

Review: Deep Learning Methods for Cybersecurity and Intrusion Detection Systems

In this paper, we are concerned with the investigation of the investigation of the various deep learning techniques employed for network intrusion detection and we introduce a deep learning framework for cybersecurity applications.

Machine Learning

Computer Vision

Uncertainty-aware deep learning methods for robust diabetic retinopathy classification

Automatic classification of diabetic retinopathy from retinal images has been widely studied using deep neural networks with impressive results. However, there is a clinical need for estimation of the

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Machine Learning

Signal Processing

A Review of Deep Learning Methods for Indoor Positioning

Deep Learning Methods for Fingerprint-Based Indoor Positioning: A Review

Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance.

This paper provides a comprehensive review of deep learning methods in indoor positioning.

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