Resource aware design of a deep convolutional-recurrent neural network for speech recognition through audio-visual sensor fusion. - Matthijs Van Keirsbilck; Bert Moons; Marian Verhelst (CoRR, 2018)

Instant Quantization of Neural Networks using Monte Carlo Methods. - Gonçalo Mordido; Matthijs Van Keirsbilck; Alexander Keller 001 (EMC2@NeurIPS, 2019)

Rethinking Full Connectivity in Recurrent Neural Networks. - Matthijs Van Keirsbilck; Alexander Keller 001; Xiaodong Yang (CoRR, 2019)

Monte Carlo Gradient Quantization. - Gonçalo Mordido; Matthijs Van Keirsbilck; Alexander Keller 001 (CVPR Workshops, 2020)

Artificial Neural Networks Generated by Low Discrepancy Sequences. - Alexander Keller 001; Matthijs Van Keirsbilck (MCQMC, 2020)

Compressing 1D Time-Channel Separable Convolutions Using Sparse Random Ternary Matrices. - Gonçalo Mordido; Matthijs Van Keirsbilck; Alexander Keller 001 (Interspeech, 2021)

Deep Learning-Based Synchronization for Uplink NB-IoT. - Fayçal Aït Aoudia; Jakob Hoydis; Sebastian Cammerer; Matthijs Van Keirsbilck; Alexander Keller 001 (GLOBECOM, 2022)

Conformer without Convolutions. - Matthijs Van Keirsbilck; Alexander Keller 001 (INTERSPEECH, 2024)

Hymba: A Hybrid-head Architecture for Small Language Models. - Xin Dong 009; Yonggan Fu; Shizhe Diao; Wonmin Byeon; Zijia Chen; Ameya Sunil Mahabaleshwarkar; Shih-Yang Liu; Matthijs Van Keirsbilck; Min-Hung Chen; Yoshi Suhara; Yingyan Celine Lin; Jan Kautz; et al. (ICLR, 2025)