Daniel Neil

According to our database, Daniel Neil authored at least 29 papers between 2014 and 2023.

Collaborative distances:

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

2023

Investigating Alternative Feature Extraction Pipelines For Clinical Note Phenotyping.

Daniel Neil

CoRR, 2023

2020

DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction.

Yuhuang Hu, Jonathan Binas, Daniel Neil, Shih-Chii Liu, Tobi Delbrück

Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

2019

Lip Reading Deep Network Exploiting Multi-Modal Spiking Visual and Auditory Sensors.

Xiaoya Li, Daniel Neil, Tobi Delbrück, Shih-Chii Liu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2019

Attention-driven Multi-sensor Selection.

Stefan Braun, Daniel Neil, Jithendar Anumula, Enea Ceolini, Shih-Chii Liu

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs.

Daniel Neil, Joss Briody, Alix Lacoste, Aaron Sim, Páidí Creed, Amir Saffari

CoRR, 2018

PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing.

Diederik Paul Moeys, Daniel Neil, Federico Corradi, Emmett Kerr, Philip J. Vance, Gautham P. Das, Sonya A. Coleman, Thomas Martin McGinnity, Dermot Kerr, Tobi Delbrück

CoRR, 2018

Multi-channel Attention for End-to-End Speech Recognition.

Stefan Braun, Daniel Neil, Jithendar Anumula, Enea Ceolini, Shih-Chii Liu

Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design.

Daniel Neil, Marwin H. S. Segler, Laura Guasch, Mohamed Ahmed, Dean Plumbley, Matthew Sellwood, Nathan Brown

Proceedings of the 6th International Conference on Learning Representations, 2018

DeltaRNN: A Power-efficient Recurrent Neural Network Accelerator.

Chang Gao, Daniel Neil, Enea Ceolini, Shih-Chii Liu, Tobi Delbrück

Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018

2017

Deep Neural Networks and Hardware Systems for Event-driven Data.

Daniel Neil

PhD thesis, 2017

ADaPTION: Toolbox and Benchmark for Training Convolutional Neural Networks with Reduced Numerical Precision Weights and Activation.

Moritz B. Milde, Daniel Neil, Alessandro Aimar, Tobi Delbrück, Giacomo Indiveri

CoRR, 2017

DDD17: End-To-End DAVIS Driving Dataset.

Jonathan Binas, Daniel Neil, Shih-Chii Liu, Tobi Delbrück

CoRR, 2017

Sensor Transformation Attention Networks.

Stefan Braun, Daniel Neil, Enea Ceolini, Jithendar Anumula, Shih-Chii Liu

CoRR, 2017

Live demonstration: Event-driven real-time spoken digit recognition system.

Jithendar Anumula, Daniel Neil, Xiaoya Li, Tobi Delbrück, Shih-Chii Liu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2017

Delta Networks for Optimized Recurrent Network Computation.

Daniel Neil, Junhaeng Lee, Tobi Delbrück, Shih-Chii Liu

Proceedings of the 34th International Conference on Machine Learning, 2017

A curriculum learning method for improved noise robustness in automatic speech recognition.

Stefan Braun, Daniel Neil, Shih-Chii Liu

Proceedings of the 25th European Signal Processing Conference, 2017

2016

Precise deep neural network computation on imprecise low-power analog hardware.

Jonathan Binas, Daniel Neil, Giacomo Indiveri, Shih-Chii Liu, Michael Pfeiffer

CoRR, 2016

Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks.

Daniel Neil, Michael Pfeiffer, Shih-Chii Liu

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences.

Daniel Neil, Michael Pfeiffer, Shih-Chii Liu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Effective sensor fusion with event-based sensors and deep network architectures.

Daniel Neil, Shih-Chii Liu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Combined frame- and event-based detection and tracking.

Hongjie Liu, Diederik Paul Moeys, Gautham P. Das, Daniel Neil, Shih-Chii Liu, Tobi Delbrück

Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Event-driven deep neural network hardware system for sensor fusion.

Ilya Kiselev, Daniel Neil, Shih-Chii Liu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Live demonstration: Event-driven deep neural network hardware system for sensor fusion.

Ilya Kiselev, Daniel Neil, Shih-Chii Liu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Steering a predator robot using a mixed frame/event-driven convolutional neural network.

Diederik Paul Moeys, Federico Corradi, Emmett Kerr, Philip J. Vance, Gautham P. Das, Daniel Neil, Dermot Kerr, Tobi Delbrück

Proceedings of the Second International Conference on Event-based Control, 2016

Temporal sequence recognition in a self-organizing recurrent network.

Enea Ceolini, Daniel Neil, Tobi Delbrück, Shih-Chii Liu

Proceedings of the Second International Conference on Event-based Control, 2016

2015

Live demonstration: Handwritten digit recognition using spiking deep belief networks on SpiNNaker.

Evangelos Stromatias, Daniel Neil, Francesco Galluppi, Michael Pfeiffer, Shih-Chii Liu, Steve B. Furber

Proceedings of the 2015 IEEE International Symposium on Circuits and Systems, 2015

Scalable energy-efficient, low-latency implementations of trained spiking Deep Belief Networks on SpiNNaker.

Evangelos Stromatias, Daniel Neil, Francesco Galluppi, Michael Pfeiffer, Shih-Chii Liu, Steve B. Furber

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing.

Peter U. Diehl, Daniel Neil, Jonathan Binas, Matthew Cook, Shih-Chii Liu, Michael Pfeiffer

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator.

Daniel Neil, Shih-Chii Liu

IEEE Trans. Very Large Scale Integr. Syst., 2014