Edward F. Chang

Cognitive Neuroscience · 2008–2022

A researcher in the Science corpus: 25 papers; trusts 21 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 64 citations into it; #1,412 of 10,852 by trust here, #984 by citations
• Artificial Intelligence — 22 citations into it
• Signal Processing — 20 citations into it
• Experimental and Cognitive Psychology — 16 citations into it; #5,240 of 9,731 by trust here, #2,388 by citations
• Model Architectures — 11 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Neuroscience — 9 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Edward F. Chang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Ilya Sutskever
2. Nima Mesgarani
3. Geoffrey E. Hinton
4. Cathy J. Price
5. Karen Simonyan
6. Yoshua Bengio
7. Alex Krizhevsky
8. Nitish Srivastava
9. Oriol Vinyals
10. Diederik P. Kingma

Who trusts Edward F. Chang overall

1. Nai Ding
2. Michael J. Crosse
3. Francis R. Willett
4. Jerry Tang
5. Gopala Krishna Anumanchipalli
6. Jonathan Z. Simon
7. Justin Riddle
8. Alyssa M. Field

Papers from Edward F. Chang's perspective

Ordered by how strongly the researchers Edward F. Chang trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Going deeper with convolutions
4. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Gradient-based learning applied to document recognition
10. Dropout: a simple way to prevent neural networks from overfitting

Their papers

• Machine translation of cortical activity to text with an encoder–decoder framework (2019) — 315 citations
• Dissecting neural computations of the human auditory pathway using deep neural networks for speech (2022)
• Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria (2021)
• Parallel and distributed encoding of speech across human auditory cortex (2021)
• Speech synthesis from neural decoding of spoken sentences (2019) — 869 citations
• The Encoding of Speech Sounds in the Superior Temporal Gyrus (2019) — 339 citations
• Human hippocampal neurogenesis drops sharply in children to undetectable levels in adults (2018) — 1,256 citations
• Neural Encoding of Auditory Features during Music Perception and Imagery (2018)
• A Spatial Map of Onset and Sustained Responses to Speech in the Human Superior Temporal Gyrus. (2018)
• Encoding of articulatory kinematic trajectories in human speech sensorimotor cortex (2018)
• Chronic ambulatory electrocorticography from human speech cortex (2017)
• Neurosurgical patients as human research subjects: ethical considerations in intracranial electrophysiology research (2017)
• Semi-automated Anatomical Labeling and Inter-subject Warping of High-Density Intracranial Recording Electrodes in Electrocorticography (2017)
• Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography (2016)
• New tools for studying microglia in the mouse and human CNS (2016) — 1,627 citations
• Towards Large-Scale Human-Based Mesoscale Neurotechnologies (2015)
• UC San Francisco UC San Francisco Previously Published Works Title Oscillatory dynamics coordinating human frontal networks in support of goal maintenance (2015)
• Phonetic Feature Encoding in Human Superior Temporal Gyrus (2014) — 954 citations
• Relationship between hospital surgical volume, lobectomy rates, and adverse perioperative events at US epilepsy centers. (2013)
• Functional Organization of Human Sensorimotor Cortex for Speech Articulation (2013) — 647 citations