Eva L. Dyer
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
18
Venues
11
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
18 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | Multi-session, multi-task neural decoding from distinct cell-types and brain regions. | Mehdi Azabou, Krystal Xuejing Pan, Vinam Arora, Ian Jarratt Knight, Eva L. Dyer, Blake Aaron Richards |
| 2025 | ICLR | In vivo cell-type and brain region classification via multimodal contrastive learning. | Han Yu, Hanrui Lyu, YiXun Xu, Charlie Windolf, Eric Kenji Lee, Fan Yang, Andrew M. Shelton, Olivier Winter, International Brain Laboratory, Eva L. Dyer, Chandramouli Chandrasekaran, Nicholas A. Steinmetz, Liam Paninski, Cole Lincoln Hurwitz |
| 2025 | ICML | Neural Encoding and Decoding at Scale. | Yizi Zhang, Yanchen Wang, Mehdi Azabou, Alexandre Andre, Zixuan Wang, Hanrui Lyu, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole Lincoln Hurwitz |
| 2024 | ICLR | GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings. | Jingyun Xiao, Ran Liu, Eva L. Dyer |
| 2024 | ICML | Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance. | Chiraag Kaushik, Ran Liu, Chi-Heng Lin, Amrit Khera, Matthew Y. Jin, Wenrui Ma, Vidya Muthukumar, Eva L. Dyer |
| 2024 | WACV | LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration. | Ran Liu, Sahil Khose, Jingyun Xiao, Lakshmi Sathidevi, Keerthan Ramnath, Zsolt Kira, Eva L. Dyer |
| 2023 | ICML | Half-Hop: A graph upsampling approach for slowing down message passing. | Mehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, Chi-Heng Lin, Lakshmi Sathidevi, Ran Liu, Michal Valko, Petar Velickovic, Eva L. Dyer |
| 2022 | ICLR | Large-Scale Representation Learning on Graphs via Bootstrapping. | Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva L. Dyer, Rmi Munos, Petar Velickovic, Michal Valko |
| 2021 | ICIP | Multi-Scale Modeling of Neural Structure in X-Ray Imagery. | Aishwarya H. Balwani, Joseph D. Miano, Ran Liu, Lindsey Kitchell, Judy A. Prasad, Erik C. Johnson, William R. Gray Roncal, Eva L. Dyer |
| 2021 | ICML | Making transport more robust and interpretable by moving data through a small number of anchor points. | Chi-Heng Lin, Mehdi Azabou, Eva L. Dyer |
| 2021 | UAI | Bayesian optimization for modular black-box systems with switching costs. | Chi-Heng Lin, Joseph D. Miano, Eva L. Dyer |
| 2020 | MICCAI | A Generative Modeling Approach for Interpreting Population-Level Variability in Brain Structure. | Ran Liu, Cem Subakan, Aishwarya H. Balwani, Jennifer D. Whitesell, Julie Harris, Sanmi Koyejo, Eva L. Dyer |
| 2019 | ACSSC | Modeling Variability in Brain Architecture with Deep Feature Learning. | Aishwarya H. Balwani, Eva L. Dyer |
| 2016 | UAI | Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes. | Mohammad Gheshlaghi Azar, Eva L. Dyer, Konrad P. Krding |
| 2016 | SDM | Deterministic Column Sampling for Low-Rank Matrix Approximation: Nystrm vs. Incomplete Cholesky Decomposition. | Raajen Patel, Tom Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk |
| 2013 | ICASSP | Subspace clustering with dense representations. | Eva L. Dyer, Christoph Studer, Richard G. Baraniuk |
| 2011 | DAC | Hybrid modeling of non-stationary process variations. | Eva L. Dyer, Mehrdad Majzoobi, Farinaz Koushanfar |
| 2010 | ITC | Rapid FPGA delay characterization using clock synthesis and sparse sampling. | Mehrdad Majzoobi, Eva L. Dyer, Ahmed Elnably, Farinaz Koushanfar |