Daniel Neil - RankMe

34 papers A* 1A 2B 3C 7Misc 1Journal 13Unranked 6

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