ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification

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The chemical industry faces mounting pressure to develop more sustainable processes while accelerating innovation to address climate challenges. Traditional discovery approaches in chemistry follow an iterative cycle: forming hypotheses about new molecules ...

Predicting and explaining the private information contained in an image in human-understandable terms is a complex and contextual task. This task is challenging even for large language models. To facilitate the understanding of privacy decisions, we propos ...

As machine learning models evolve, maintaining transparency demands more human-centric explainable AI techniques. Counterfactual explanations, with roots in human reasoning, identify the minimal input changes needed to obtain a given output, and hence, are ...

Background: The integration of artificial intelligence (AI) into health care has become a crucial element in the digital transformation of health systems worldwide. Despite the potential benefits across diverse medical domains, a significant barrier to the ...

Vision-language models (VLMs) are typically composed of a vision encoder, e.g. CLIP, and a language model (LM) that interprets the encoded features to solve downstream tasks. Despite remarkable progress, VLMs are subject to several shortcomings due to the ...

The spinal cord plays a central role in regulating sensorimotor functions through complex neural pathways. However, detailed investigation of these mechanisms remains a developing field. In this study, we propose a multimodal approach combining transcrania ...

The Emo-FilM dataset stands for Emotion research using Films and fMRI in healthy participants. This dataset includes emotion annotations by 44 raters for 14 short films with a combined duration of over 2 1/2 hours and recordings of respiration, heart rate, ...

This dataset was created as part of the PhD project Machine Understanding of Architectural Space: From Analytical to Generative Applications at EPFL Media and Design Lab (LDM). It was derived from the Cubicasa5K dataset. The dataset contains preprocessed d ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

In this paper, three machine learning (ML)-based approaches—XGBoost, Artificial Neural Network (ANN), and Random Forest algorithms—are compared for the localization of lightning through the analysis of lightninginduced voltages on power transmission lines. ...

Irregular sampling of time series in electronic health records (EHRs) is one of the main challenges for developing machine learning models. Additionally, the pattern of missing values in certain clinical variables is not at random but depends on the decisi ...

Drug design is both a time consuming and expensive endeavour. Computational strategies offer viable options to address this task; deep learning approaches in particular are indeed gaining traction for their capability of dealing with chemical structures. A ...

We experimentally study the spectral lasing response of on-chip InP network random lasers under illumination of different input image shapes. Deep-learning models have become increasingly omipresent throughout society. However, they are blighted by exponen ...

Creators Meystre Julie Olivier Burri Contributors Jean Jacquemier Description This dataset contains 7 QuPath projects. The raw data images linked to these projects and located in other Zenodo datasets need to be downloaded as well. The raw data contains im ...

Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we ...

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome densities, ...

Human hands are highly articulated and versatile at handling objects. Jointly estimating the 3D poses of a hand and the object it manipulates from a monocular camera is challenging due to frequent occlusions. Thus, existing methods often rely on intermedia ...

Porous membranes are thin solid structures that allow the flow to pass through their tiny openings, called pores. Flow inertia may play a significant role in several filtration flows of natural and engineering interest. Here, we develop a predictive macros ...

The tribocorrosion property of tungsten plays a great role in the chemical mechanical polishing of tungsten plugs used in integrated circuits. This study applied a lubricated tribocorrosion model to tungsten, verified and calibrated the model using results ...

This paper extends the authors' previous work on Control by Interconnection - Model Predictive Control (CbI-MPC) design for constrained port-Hamiltonian systems to deal with the unmeasurable system states. The first contribution resides in the CbI-oriented ...

ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification

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Integrating AI across the Chemistry Discovery Cycle: Advancing Sustainable Chemistry through Digital Methods

Image-Guided Topic Modeling for Interpretable Privacy Classification

Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments

Finding Consensus on Trust in AI in Health Care: Recommendations From a Panel of International Experts

BRAVE: Broadening the Visual Encoding of Vision-Language Models

Improved Spinal Cord FMRI Activation Mapping Using Regularized Hemodynamic Deconvolution

Emo-film: a Multimodal Dataset for Affective Neuroscience Using Naturalistic Stimuli

Floorplan Isovist Dataset

Machine learning-aided generative molecular design

An Efficient Machine Learning Model for Lightning Localization via Lightning-Induced Voltages on Transmission Lines

TEE4EHR: Transformer event encoder for better representation learning in electronic health records

AMCG: a graph dual atomic-molecular conditional molecular generator

Image sensitive spectral response of semiconductor random network lasers

Supplementary files for Machine learning for histological annotation and quantification of cortical layers

Self-supervised learning of wrist-worn daily living accelerometer data improves the automated detection of gait in older adults

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields

Quasi-linear homogenization for large-inertia laminar transport across permeable membranes

Assessing the wear degradation of tungsten in acidic solutions using a lubricated tribocorrosion model

Port-Hamiltonian observer for state-feedback control design