Eva L. Dyer
Affiliations:- Georgia Institute of Technology, Atlanta, GA, USA
- Emory University, Atlanta, GA, USA
According to our database1,
Eva L. Dyer
authored at least 44 papers
between 2007 and 2024.
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Bibliography
2024
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective.
J. Mach. Learn. Res., 2024
CoRR, 2024
Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution.
CoRR, 2024
LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Detecting change points in neural population activity with contrastive metric learning.
Proceedings of the 11th International IEEE/EMBS Conference on Neural Engineering, 2023
Proceedings of the 11th International IEEE/EMBS Conference on Neural Engineering, 2023
Proceedings of the International Conference on Machine Learning, 2023
2022
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
CoRR, 2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Making transport more robust and interpretable by moving data through a small number of anchor points.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021
2020
Pyglmnet: Python implementation of elastic-net regularized generalized linear models.
J. Open Source Softw., 2020
A Generative Modeling Approach for Interpreting Population-Level Variability in Brain Structure.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019
2018
IEEE Trans. Neural Networks Learn. Syst., 2018
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018
2016
CoRR, 2016
Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
Deterministic Column Sampling for Low-Rank Matrix Approximation: Nyström vs. Incomplete Cholesky Decomposition.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016
2015
CoRR, 2015
2013
Proceedings of the IEEE International Conference on Acoustics, 2013
2011
Proceedings of the 48th Design Automation Conference, 2011
2010
Proceedings of the 2011 IEEE International Test Conference, 2010
Recovering Spikes from Noisy Neuronal Calcium Signals via Structured Sparse Approximation.
Proceedings of the Latent Variable Analysis and Signal Separation, 2010
2007
Proceedings of the Medicine Meets Virtual Reality 15, 2007