Function approximation with uncertainty propagation in a VLSI spiking neural network. - Dane S. Corneil; Daniel Sonnleithner; Emre Neftci; Elisabetta Chicca; Matthew Cook 001; Giacomo Indiveri; Rodney J. Douglas (IJCNN, 2012)

Real-time inference in a VLSI spiking neural network. - Dane S. Corneil; Daniel Sonnleithner; Emre Neftci; Elisabetta Chicca; Matthew Cook 001; Giacomo Indiveri; Rodney J. Douglas (ISCAS, 2012)

Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze-like Environments. - Dane S. Corneil; Wulfram Gerstner (NIPS, 2015)

Efficient ModelBased Deep Reinforcement Learning with Variational State Tabulation. - Dane S. Corneil; Wulfram Gerstner; Johanni Brea (ICML, 2018)

Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation. - Dane S. Corneil; Wulfram Gerstner; Johanni Brea (CoRR, 2018)

Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks. - Roman Pogodin; Dane S. Corneil; Alexander Seeholzer; Joseph Heng; Wulfram Gerstner (CoRR, 2019)

On Masked Language Models for Contextual Link Prediction. - Angus Brayne; Maciej Wiatrak; Dane S. Corneil (DeeLIO@ACL, 2022)

Retrieve to Explain: Evidence-driven Predictions with Language Models. - Ravi Patel; Angus Brayne; Rogier Hintzen; Daniel Jaroslawicz; Georgiana Neculae; Dane S. Corneil (CoRR, 2024)

Retrieve to Explain: Evidence-driven Predictions for Explainable Drug Target Identification. - Ravi Patel; Angus Brayne; Rogier Hintzen; Daniel Jaroslawicz; Georgiana Neculae; Dane S. Corneil (ACL (1), 2025)