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Ard Kastrati

4 accepted papers

2026

ADAPTING NEURAL AUDIO CODECS TO EEG

ICASSP 2026poster

EEG and audio are inherently distinct modalities, differing in sampling rate, channel structure, and scale. Yet, we show that pretrained neural audio codecs can serve as effective starting points for EEG compression, provided that the data are preprocessed to be suitable to the codec's input constra…

Cited by 0SourcePDFScholar
2022

A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications

ICML 2022spotlight

The collection of eye gaze information provides a window into many critical aspects of human cognition, health and behaviour. Additionally, many neuroscientific studies complement the behavioural information gained from eye tracking with the high temporal resolution and neurophysiological markers pr…

2022

FACT: Learning Governing Abstractions Behind Integer Sequences

NeurIPS 2022accept

Integer sequences are of central importance to the modeling of concepts admitting complete finitary descriptions. We introduce a novel view on the learning of such concepts and lay down a set of benchmarking tasks aimed at conceptual understanding by machine learning models. These tasks indirectly a…

Cited by 5SourcePDFScholar
2021

EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction

NeurIPS 2021poster

We present a new dataset and benchmark with the goal of advancing research in the intersection of brain activities and eye movements. Our dataset, EEGEyeNet, consists of simultaneous Electroencephalography (EEG) and Eye-tracking (ET) recordings from 356 different subjects collected from three differ…

Cited by 55SourcecodeScholar