activity
20192025
most citedBreaking the Limits of Message Passing Graph Neural Networks

28 citations · 34 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20221 cited

Reducing The Mismatch Between Marginal and Learned Distributions in Neural Video Compression

Muhammet Balcilar, Bharath Bhushan Damodaran, Pierre Hellier

During the last four years, we have witnessed the success of end-to-end trainable models for image compression. Compared to decades of incremental work, these machine learning (ML)…

eess.IV2022

Improving The Reconstruction Quality by Overfitted Decoder Bias in Neural Image Compression

Oussama Jourairi, Muhammet Balcilar, Anne Lambert +1

End-to-end trainable models have reached the performance of traditional handcrafted compression techniques on videos and images. Since the parameters of these models are learned ov…

cs.LG202128 cited

Breaking the Limits of Message Passing Graph Neural Networks

Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère +3

Since the Message Passing (Graph) Neural Networks (MPNNs) have a linear complexity with respect to the number of nodes when applied to sparse graphs, they have been widely implemen…

cs.LG2020

Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks

Muhammet Balcilar, Guillaume Renton, Pierre Heroux +3

This paper aims at revisiting Graph Convolutional Neural Networks by bridging the gap between spectral and spatial design of graph convolutions. We theoretically demonstrate some e…

cs.LG20195 cited

Audio Captcha Recognition Using RastaPLP Features by SVM

Ahmet Faruk Cakmak, Muhammet Balcilar

Nowadays, CAPTCHAs are computer generated tests that human can pass but current computer systems can not. They have common usage in various web services in order to be able to dete…