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ORCIDDaniel Neil
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2020 – today
- 2023
[i12]Daniel Neil:
Investigating Alternative Feature Extraction Pipelines For Clinical Note Phenotyping. CoRR abs/2310.03772 (2023)- 2020
- [c20]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: 1-6 - [i11]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 abs/2005.08605 (2020)
2010 – 2019
- 2019
- [c19]Stefan Braun, Daniel Neil, Jithendar Anumula, Enea Ceolini
, Shih-Chii Liu:
Attention-driven Multi-sensor Selection. IJCNN 2019: 1-8 - [c18]Xiaoya Li, Daniel Neil, Tobi Delbrück, Shih-Chii Liu:
Lip Reading Deep Network Exploiting Multi-Modal Spiking Visual and Auditory Sensors. ISCAS 2019: 1-5 - 2018
- [c17]Chang Gao, Daniel Neil, Enea Ceolini, Shih-Chii Liu, Tobi Delbrück:
DeltaRNN: A Power-efficient Recurrent Neural Network Accelerator. FPGA 2018: 21-30 - [c16]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 - [c15]Stefan Braun, Daniel Neil, Jithendar Anumula, Enea Ceolini, Shih-Chii Liu:
Multi-channel Attention for End-to-End Speech Recognition. INTERSPEECH 2018: 17-21 - [i10]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 abs/1807.03128 (2018) - [i9]Daniel Neil, Joss Briody, Alix Lacoste, Aaron Sim, Páidí Creed, Amir Saffari:
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs. CoRR abs/1812.00279 (2018) - 2017
- [b1]Daniel Neil:
Deep Neural Networks and Hardware Systems for Event-driven Data. ETH Zurich, Zürich, Switzerland, 2017 - [c14]Stefan Braun, Daniel Neil, Shih-Chii Liu:
A curriculum learning method for improved noise robustness in automatic speech recognition. EUSIPCO 2017: 548-552 - [c13]Daniel Neil, Junhaeng Lee, Tobi Delbrück, Shih-Chii Liu:
Delta Networks for Optimized Recurrent Network Computation. ICML 2017: 2584-2593 - [c12]Jithendar Anumula, Daniel Neil, Xiaoya Li, Tobi Delbrück, Shih-Chii Liu:
Live demonstration: Event-driven real-time spoken digit recognition system. ISCAS 2017: 1 - [i8]Stefan Braun, Daniel Neil, Enea Ceolini, Jithendar Anumula, Shih-Chii Liu:
Sensor Transformation Attention Networks. CoRR abs/1708.01015 (2017) - [i7]Jonathan Binas, Daniel Neil, Shih-Chii Liu, Tobi Delbrück:
DDD17: End-To-End DAVIS Driving Dataset. CoRR abs/1711.01458 (2017) - [i6]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 abs/1711.04713 (2017) - 2016
- [c11]Enea Ceolini, Daniel Neil, Tobi Delbrück, Shih-Chii Liu:
Temporal sequence recognition in a self-organizing recurrent network. EBCCSP 2016: 1-4 - [c10]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: 1-8 - [c9]Ilya Kiselev, Daniel Neil, Shih-Chii Liu:
Live demonstration: Event-driven deep neural network hardware system for sensor fusion. ISCAS 2016: 452 - [c8]Daniel Neil, Shih-Chii Liu:
Effective sensor fusion with event-based sensors and deep network architectures. ISCAS 2016: 2282-2285 - [c7]Ilya Kiselev, Daniel Neil, Shih-Chii Liu:
Event-driven deep neural network hardware system for sensor fusion. ISCAS 2016: 2495-2498 - [c6]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: 2511-2514 - [c5]Daniel Neil, Michael Pfeiffer, Shih-Chii Liu:
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. NIPS 2016: 3882-3890 - [c4]Daniel Neil, Michael Pfeiffer, Shih-Chii Liu:
Learning to be efficient: algorithms for training low-latency, low-compute deep spiking neural networks. SAC 2016: 293-298 - [i5]Stefan Braun, Daniel Neil, Shih-Chii Liu:
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition. CoRR abs/1606.06864 (2016) - [i4]Jonathan Binas, Daniel Neil, Giacomo Indiveri, Shih-Chii Liu, Michael Pfeiffer:
Precise deep neural network computation on imprecise low-power analog hardware. CoRR abs/1606.07786 (2016) - [i3]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 abs/1606.09433 (2016) - [i2]Daniel Neil, Michael Pfeiffer, Shih-Chii Liu:
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences. CoRR abs/1610.09513 (2016) - [i1]Daniel Neil, Junhaeng Lee, Tobi Delbrück, Shih-Chii Liu:
Delta Networks for Optimized Recurrent Network Computation. CoRR abs/1612.05571 (2016) - 2015
- [c3]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: 1-8 - [c2]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: 1-8 - [c1]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: 1901 - 2014
- [j1]Daniel Neil, Shih-Chii Liu:
Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator. IEEE Trans. Very Large Scale Integr. Syst. 22(12): 2621-2628 (2014)
Coauthor Index
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