Daniel Neil

Publication Activity (10 Years)

Years Active: 2014-2023
Publications (10 Years): 29

Top Topics

Speech Recognition

Deep Belief Networks

Top Venues

Publications

Daniel Neil
Investigating Alternative Feature Extraction Pipelines For Clinical Note Phenotyping. CoRR (2023)
Yuhuang Hu, Jonathan Binas, Daniel Neil, Shih-Chii Liu, Tobi Delbrück
DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction. CoRR (2020)
Yuhuang Hu, Jonathan Binas, Daniel Neil, Shih-Chii Liu, Tobi Delbrück
DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction. ITSC (2020)
Xiaoya Li, Daniel Neil, Tobi Delbrück, Shih-Chii Liu
Lip Reading Deep Network Exploiting Multi-Modal Spiking Visual and Auditory Sensors. ISCAS (2019)
Stefan Braun, Daniel Neil, Jithendar Anumula, Enea Ceolini, Shih-Chii Liu
Attention-driven Multi-sensor Selection. IJCNN (2019)
Daniel Neil, Joss Briody, Alix Lacoste, Aaron Sim, Páidí Creed, Amir Saffari
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs. CoRR (2018)
Stefan Braun, Daniel Neil, Jithendar Anumula, Enea Ceolini, Shih-Chii Liu
Multi-channel Attention for End-to-End Speech Recognition. INTERSPEECH (2018)
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
PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing. CoRR (2018)
Chang Gao, Daniel Neil, Enea Ceolini, Shih-Chii Liu, Tobi Delbrück
DeltaRNN: A Power-efficient Recurrent Neural Network Accelerator. FPGA (2018)
Daniel Neil, Marwin H. S. Segler, Laura Guasch, Mohamed Ahmed, Dean Plumbley, Matthew Sellwood, Nathan Brown
Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design. ICLR (Workshop) (2018)
Stefan Braun, Daniel Neil, Shih-Chii Liu
A curriculum learning method for improved noise robustness in automatic speech recognition. EUSIPCO (2017)
Moritz B. Milde, Daniel Neil, Alessandro Aimar, Tobi Delbrück, Giacomo Indiveri
ADaPTION: Toolbox and Benchmark for Training Convolutional Neural Networks with Reduced Numerical Precision Weights and Activation. CoRR (2017)
Daniel Neil, Junhaeng Lee, Tobi Delbrück, Shih-Chii Liu
Delta Networks for Optimized Recurrent Network Computation. ICML (2017)
Jonathan Binas, Daniel Neil, Shih-Chii Liu, Tobi Delbrück
DDD17: End-To-End DAVIS Driving Dataset. CoRR (2017)
Stefan Braun, Daniel Neil, Enea Ceolini, Jithendar Anumula, Shih-Chii Liu
Sensor Transformation Attention Networks. CoRR (2017)
Jithendar Anumula, Daniel Neil, Xiaoya Li, Tobi Delbrück, Shih-Chii Liu
Live demonstration: Event-driven real-time spoken digit recognition system. ISCAS (2017)
Diederik Paul Moeys, Federico Corradi, Emmett Kerr, Philip J. Vance, Gautham P. Das, Daniel Neil, Dermot Kerr, Tobi Delbrück
Steering a Predator Robot using a Mixed Frame/Event-Driven Convolutional Neural Network. CoRR (2016)
Stefan Braun, Daniel Neil, Shih-Chii Liu
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition. CoRR (2016)
Enea Ceolini, Daniel Neil, Tobi Delbrück, Shih-Chii Liu
Temporal sequence recognition in a self-organizing recurrent network. EBCCSP (2016)
Hongjie Liu, Diederik Paul Moeys, Gautham P. Das, Daniel Neil, Shih-Chii Liu, Tobi Delbrück
Combined frame- and event-based detection and tracking. ISCAS (2016)
Diederik Paul Moeys, Federico Corradi, Emmett Kerr, Philip J. Vance, Gautham P. Das, Daniel Neil, Dermot Kerr, Tobi Delbrück
Steering a predator robot using a mixed frame/event-driven convolutional neural network. EBCCSP (2016)
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks. SAC (2016)
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. CoRR (2016)
Daniel Neil, Shih-Chii Liu
Effective sensor fusion with event-based sensors and deep network architectures. ISCAS (2016)
Ilya Kiselev, Daniel Neil, Shih-Chii Liu
Live demonstration: Event-driven deep neural network hardware system for sensor fusion. ISCAS (2016)
Jonathan Binas, Daniel Neil, Giacomo Indiveri, Shih-Chii Liu, Michael Pfeiffer
Precise deep neural network computation on imprecise low-power analog hardware. CoRR (2016)
Daniel Neil, Michael Pfeiffer, Shih-Chii Liu
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. NIPS (2016)
Daniel Neil, Junhaeng Lee, Tobi Delbrück, Shih-Chii Liu
Delta Networks for Optimized Recurrent Network Computation. CoRR (2016)
Ilya Kiselev, Daniel Neil, Shih-Chii Liu
Event-driven deep neural network hardware system for sensor fusion. ISCAS (2016)
Evangelos Stromatias, Daniel Neil, Francesco Galluppi, Michael Pfeiffer, Shih-Chii Liu, Steve B. Furber
Scalable energy-efficient, low-latency implementations of trained spiking Deep Belief Networks on SpiNNaker. IJCNN (2015)
Peter U. Diehl, Daniel Neil, Jonathan Binas, Matthew Cook, Shih-Chii Liu, Michael Pfeiffer
Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. IJCNN (2015)
Evangelos Stromatias, Daniel Neil, Francesco Galluppi, Michael Pfeiffer, Shih-Chii Liu, Steve B. Furber
Live demonstration: Handwritten digit recognition using spiking deep belief networks on SpiNNaker. ISCAS (2015)
Daniel Neil, Shih-Chii Liu
Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator. IEEE Trans. Very Large Scale Integr. Syst. 22 (12) (2014)