Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator. - Daniel Neil; Shih-Chii Liu (IEEE Trans. Very Large Scale Integr. Syst., 2014)

Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. - Peter U. Diehl; Daniel Neil; Jonathan Binas; Matthew Cook 001; Shih-Chii Liu; Michael Pfeiffer 001 (IJCNN, 2015)

Scalable energy-efficient, low-latency implementations of trained spiking Deep Belief Networks on SpiNNaker. - Evangelos Stromatias; Daniel Neil; Francesco Galluppi; Michael Pfeiffer 001; Shih-Chii Liu; Steve B. Furber (IJCNN, 2015)

Live demonstration: Handwritten digit recognition using spiking deep belief networks on SpiNNaker. - Evangelos Stromatias; Daniel Neil; Francesco Galluppi; Michael Pfeiffer 001; Shih-Chii Liu; Steve B. Furber (ISCAS, 2015)

Temporal sequence recognition in a self-organizing recurrent network. - Enea Ceolini; Daniel Neil; Tobi Delbruck; Shih-Chii Liu (EBCCSP, 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 (EBCCSP, 2016)

Live demonstration: Event-driven deep neural network hardware system for sensor fusion. - Ilya Kiselev; Daniel Neil; Shih-Chii Liu (ISCAS, 2016)

Event-driven deep neural network hardware system for sensor fusion. - Ilya Kiselev; Daniel Neil; Shih-Chii Liu (ISCAS, 2016)

Combined frame- and event-based detection and tracking. - Hongjie Liu; Diederik Paul Moeys; Gautham P. Das; Daniel Neil; Shih-Chii Liu; Tobi Delbrück (ISCAS, 2016)

Effective sensor fusion with event-based sensors and deep network architectures. - Daniel Neil; Shih-Chii Liu (ISCAS, 2016)

Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. - Daniel Neil; Michael Pfeiffer 001; Shih-Chii Liu (NIPS, 2016)

Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks. - Daniel Neil; Michael Pfeiffer 001; Shih-Chii Liu (SAC, 2016)

Precise deep neural network computation on imprecise low-power analog hardware. - Jonathan Binas; Daniel Neil; Giacomo Indiveri; Shih-Chii Liu; Michael Pfeiffer 001 (CoRR, 2016)

A curriculum learning method for improved noise robustness in automatic speech recognition. - Stefan Braun 005; Daniel Neil; Shih-Chii Liu (EUSIPCO, 2017)

Delta Networks for Optimized Recurrent Network Computation. - Daniel Neil; Junhaeng Lee; Tobi Delbruck; Shih-Chii Liu (ICML, 2017)

Live demonstration: Event-driven real-time spoken digit recognition system. - Jithendar Anumula; Daniel Neil; Xiaoya Li; Tobi Delbruck; Shih-Chii Liu (ISCAS, 2017)

Sensor Transformation Attention Networks. - Stefan Braun 005; Daniel Neil; Enea Ceolini; Jithendar Anumula; Shih-Chii Liu (CoRR, 2017)

DDD17: End-To-End DAVIS Driving Dataset. - Jonathan Binas; Daniel Neil; Shih-Chii Liu; Tobi Delbruck (CoRR, 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 Delbruck; Giacomo Indiveri (CoRR, 2017)

Deep Neural Networks and Hardware Systems for Event-driven Data. - Daniel Neil (2017)

DeltaRNN: A Power-efficient Recurrent Neural Network Accelerator. - Chang Gao 002; Daniel Neil; Enea Ceolini; Shih-Chii Liu; Tobi Delbruck (FPGA, 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 (ICLR (Workshop), 2018)

Multi-channel Attention for End-to-End Speech Recognition. - Stefan Braun 005; Daniel Neil; Jithendar Anumula; Enea Ceolini; Shih-Chii Liu (INTERSPEECH, 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 Delbruck (CoRR, 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)

Attention-driven Multi-sensor Selection. - Stefan Braun 005; Daniel Neil; Jithendar Anumula; Enea Ceolini; Shih-Chii Liu (IJCNN, 2019)

Lip Reading Deep Network Exploiting Multi-Modal Spiking Visual and Auditory Sensors. - Xiaoya Li; Daniel Neil; Tobi Delbruck; Shih-Chii Liu (ISCAS, 2019)

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 Delbruck (ITSC, 2020)

Investigating Alternative Feature Extraction Pipelines For Clinical Note Phenotyping. - Daniel Neil (CoRR, 2023)