Multi-instrument musical transcription using a dynamic graphical model. - Brian K. Vogel; Michael I. Jordan; David Wessel (ICASSP (5), 2005)

Positive factor networks: A graphical framework for modeling non-negative sequential data - Brian K. Vogel (CoRR, 2008)

Parameter Reference Loss for Unsupervised Domain Adaptation. - Jiren Jin; Richard G. Calland; Takeru Miyato; Brian K. Vogel; Hideki Nakayama (CoRR, 2017)

Unimanual Pen+Touch Input Using Variations of Precision Grip Postures. - Drini Cami; Fabrice Matulic; Richard G. Calland; Brian K. Vogel; Daniel Vogel 001 (UIST, 2018)

Chainer: A Deep Learning Framework for Accelerating the Research Cycle. - Seiya Tokui; Ryosuke Okuta; Takuya Akiba; Yusuke Niitani; Toru Ogawa; Shunta Saito; Shuji Suzuki; Kota Uenishi; Brian Vogel; Hiroyuki Yamazaki Vincent (KDD, 2019)

Eliciting Pen-Holding Postures for General Input with Suitability for EMG Armband Detection. - Fabrice Matulic; Brian K. Vogel; Naoki Kimura; Daniel Vogel 001 (ISS, 2019)

Adaptive Loss Scaling for Mixed Precision Training. - Ruizhe Zhao; Brian Vogel; Tanvir Ahmed (CoRR, 2019)

PenSight: Enhanced Interaction with a Pen-Top Camera. - Fabrice Matulic; Riku Arakawa; Brian K. Vogel; Daniel Vogel 001 (CHI, 2020)

Reducing Underflow in Mixed Precision Training by Gradient Scaling. - Ruizhe Zhao; Brian Vogel; Tanvir Ahmed; Wayne Luk (IJCAI, 2020)

MN-Core - A Highly Efficient and Scalable Approach to Deep Learning. - Ken Namura; Johannes Maximilian Kühn; Tohru Adachi; H. Imachi; H. Kaneko; T. Kato; Go Watanabe; Naoto Tanaka; S. Kashihara; Hiroshi Miyashita; Y. Tomonaga; Ryosuke Okuta; et al. (VLSI Circuits, 2021)

An NMF-Based Building Block for Interpretable Neural Networks With Continual Learning. - Brian K. Vogel (CoRR, 2023)