David D. Cox
Orcid: 0000-0002-2189-9743Affiliations:
- MIT-IBM Watson AI Lab, Cambridge, MA, USA
- Harvard University, Center for Brain Science, Cambridge, MA, USA (former)
- Massachusetts Institute of Technology (MIT), Department of Brain and Cognitive Sciences, Cambridge, MA, USA (PhD)
According to our database1,
David D. Cox
authored at least 88 papers
between 2003 and 2024.
Collaborative distances:
Collaborative distances:
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on coxlab.org
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Bibliography
2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Findings of the Association for Computational Linguistics, 2024
2023
CoRR, 2023
Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023
2022
CoRR, 2022
ContentVec: An Improved Self-Supervised Speech Representation by Disentangling Speakers.
Proceedings of the International Conference on Machine Learning, 2022
On the Interplay between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis.
Proceedings of the IEEE International Conference on Acoustics, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Embodied Concept Learner: Self-supervised Learning of Concepts and Mapping through Instruction Following.
Proceedings of the Conference on Robot Learning, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks.
Neural Comput., 2021
Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
A neural network trained for prediction mimics diverse features of biological neurons and perception.
Nat. Mach. Intell., 2020
Improving the Reconstruction of Disentangled Representation Learners via Multi-Stage Modelling.
CoRR, 2020
Experiences and Insights for Collaborative Industry-Academic Research in Artificial Intelligence.
AI Mag., 2020
Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Proceedings of the 3rd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages, 2019
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal Aggregation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
2018
CoRR, 2018
A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception.
CoRR, 2018
Proceedings of the Image Analysis for Moving Organ, Breast, and Thoracic Images, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
A System for Accurate Tracking and Video Recordings of Rodent Eye Movements using Convolutional Neural Networks for Biomedical Image Segmentation.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018
2017
Proceedings of the International Conference for High Performance Computing, 2017
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017
Proceedings of the 5th International Conference on Learning Representations, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
2015
Model selection for Discriminative Restricted Boltzmann Machines through meta-heuristic techniques.
J. Comput. Sci., 2015
Measuring and Understanding Sensory Representations within Deep Networks Using a Numerical Optimization Framework.
CoRR, 2015
CoRR, 2015
On the Model Selection of Bernoulli Restricted Boltzmann Machines Through Harmony Search.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2015
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2015
2014
IEEE Trans. Inf. Forensics Secur., 2014
IEEE Trans. Pattern Anal. Mach. Intell., 2014
J. Field Robotics, 2014
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014
Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
2013
Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be?
CoRR, 2013
Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms.
Proceedings of the 12th Python in Science Conference, 2013
Proceedings of the 12th Python in Science Conference, 2013
Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures.
Proceedings of the 30th International Conference on Machine Learning, 2013
Proceedings of the International Conference on Biometrics, 2013
2012
High-throughput-derived biologically-inspired features for unconstrained face recognition.
Image Vis. Comput., 2012
Proceedings of the 19th IEEE International Conference on Image Processing, 2012
Space-Variant Descriptor Sampling for Action Recognition Based on Saliency and Eye Movements.
Proceedings of the Computer Vision - ECCV 2012, 2012
Proceedings of the British Machine Vision Conference, 2012
2011
Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV 2011), 2011
Beyond simple features: A large-scale feature search approach to unconstrained face recognition.
Proceedings of the Ninth IEEE International Conference on Automatic Face and Gesture Recognition (FG 2011), 2011
Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011
2010
Proceedings of the International Conference on Field-Programmable Technology, 2010
An Evaluation of the Invariance Properties of a Biologically-Inspired System for Unconstrained Face Recognition.
Proceedings of the Bio-Inspired Models of Network, Information, and Computing Systems, 2010
2009
A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation.
PLoS Comput. Biol., 2009
How far can you get with a modern face recognition test set using only simple features?.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009
2008
2003
Functional magnetic resonance imaging (fMRI) "brain reading": detecting and classifying distributed patterns of fMRI activity in human visual cortex.
NeuroImage, 2003