Adam D. Cobb
Orcid: 0000-0003-2868-6983
According to our database1,
Adam D. Cobb
authored at least 37 papers
between 2017 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
2024
Proceedings of the IEEE Military Communications Conference, 2024
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Mach. Learn., 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the IEEE Military Communications Conference, 2023
Proceedings of Cyber-Physical Systems and Internet of Things Week 2023, 2023
2022
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning.
CoRR, 2022
URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference methods.
Proceedings of the Fifth Conference on Machine Learning and Systems, 2022
Proceedings of the International Conference on Machine Learning, 2022
2021
Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks.
Proceedings of the Winter Simulation Conference, 2021
Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splitting.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Proceedings of the IEEE Congress on Evolutionary Computation, 2021
2020
PhD thesis, 2020
Better call Surrogates: A hybrid Evolutionary Algorithm for Hyperparameter optimization.
CoRR, 2020
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks.
CoRR, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Proceedings of the 2nd IEEE International Conference on Cognitive Machine Intelligence, 2020
2019
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo.
CoRR, 2019
CoRR, 2019
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019
2018
Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer's disease severity.
CoRR, 2018
Proceedings of the Scalable Uncertainty Management - 12th International Conference, 2018
Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
2017
CoRR, 2017