Dane S. Corneil

According to our database, Dane S. Corneil authored at least 9 papers between 2012 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Retrieve to Explain: Evidence-driven Predictions for Explainable Drug Target Identification.

Ravi Patel, Angus Brayne, Rogier Hintzen, Daniel Jaroslawicz, Georgiana Neculae, Dane S. Corneil

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Retrieve to Explain: Evidence-driven Predictions with Language Models.

Ravi Patel, Angus Brayne, Rogier Hintzen, Daniel Jaroslawicz, Georgiana Neculae, Dane S. Corneil

CoRR, 2024

2022

On Masked Language Models for Contextual Link Prediction.

Angus Brayne, Maciej Wiatrak, Dane S. Corneil

Proceedings of Deep Learning Inside Out: The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, 2022

2019

Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks.

Roman Pogodin, Dane S. Corneil, Alexander Seeholzer, Joseph Heng, Wulfram Gerstner

CoRR, 2019

2018

Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation.

Dane S. Corneil, Wulfram Gerstner, Johanni Brea

CoRR, 2018

Efficient ModelBased Deep Reinforcement Learning with Variational State Tabulation.

Dane S. Corneil, Wulfram Gerstner, Johanni Brea

Proceedings of the 35th International Conference on Machine Learning, 2018

2015

Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze-like Environments.

Dane S. Corneil, Wulfram Gerstner

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2012

Real-time inference in a VLSI spiking neural network.

Dane S. Corneil, Daniel Sonnleithner, Emre Neftci, Elisabetta Chicca, Matthew Cook, Giacomo Indiveri, Rodney J. Douglas

Proceedings of the 2012 IEEE International Symposium on Circuits and Systems, 2012

Function approximation with uncertainty propagation in a VLSI spiking neural network.

Dane S. Corneil, Daniel Sonnleithner, Emre Neftci, Elisabetta Chicca, Matthew Cook, Giacomo Indiveri, Rodney J. Douglas

Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012