Eva L. Dyer

1. Large-Scale Representation Learning on Graphs via Bootstrapping
   2021/02/12 by Shantanu Thakoor, Corentin Tallec, Thakoor, Shantanu +13 · 16 citations
   Computer Science · Decision Sciences · #Advanced Graph Neural Networks #Topic Modeling #Data Quality and Management
2. Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity
   2021/09/09 by Felix Pei, Joel Ye, Pei, Felix +29 · 13 citations
   Neuroscience · #Neural dynamics and brain function #EEG and Brain-Computer Interfaces #Functional Brain Connectivity Studies
3. A Unified, Scalable Framework for Neural Population Decoding
   2023/10/24 by Mehdi Azabou, Vinam Arora, Azabou, Mehdi +17 · 20 citations
   Neuroscience · Computer Science · Biochemistry, Genetics and Molecular Biology · #Neural dynamics and brain function #Neural Networks and Applications #Cell Image Analysis Techniques
4. Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers
   2022/06/10 by Ran Liu, Liu, Ran, Mehdi Azabou +7 · 5 citations
   Computer Science · Neuroscience · #FOS: Biological sciences #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Neural Networks and Applications #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC)
5. Why the simplest explanation isn’t always the best
   2023/12/20 by Eva L. Dyer, Konrad P. Körding · 2 voices · 4 citations
   Neuroscience · Computer Science · #Neural dynamics and brain function #Cognitive Science and Education Research #Time Series Analysis and Forecasting
6. Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity
   2021/11/03 by Ran Liu, Mehdi Azabou, Liu, Ran +13 · 3 citations
   Neuroscience · Engineering · #Neural dynamics and brain function #Advanced Memory and Neural Computing #EEG and Brain-Computer Interfaces
7. Mine Your Own vieW: Self-Supervised Learning Through Across-Sample\n Prediction
   2021/02/19 by Mehdi Azabou, Azabou, Mehdi, Mohammad Gheshlaghi Azar +23 · 6 citations
   Biochemistry, Genetics and Molecular Biology · Computer Science · #AI in cancer detection #Cell Image Analysis Techniques #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Multimodal Machine Learning Applications
8. GraphFM: A generalist graph transformer that learns transferable representations across diverse domains
   2024/07/16 by Divyansha Lachi, Mehdi Azabou, Lachi, Divyansha +5 · 5 citations
   Computer Science · #Model-Driven Software Engineering Techniques #Software Testing and Debugging Techniques #Teaching and Learning Programming
9. Generalizable, real-time neural decoding with hybrid state-space models
   2025/06/05 by Avery Hee-Woon Ryoo, Ryoo, Avery Hee-Woon, Nanda H. Krishna +11 · 2 voices · 4 citations
   Medicine · Neuroscience · #EEG and Brain-Computer Interfaces #Neural dynamics and brain function #Neurological disorders and treatments #cs.LG #q-bio.NC
10. Half-Hop: A graph upsampling approach for slowing down message passing
    2023/08/17 by Mehdi Azabou, Azabou, Mehdi, Venkataramana Ganesh +15 · 2 citations
    Computer Science · Neuroscience · #Brain Tumor Detection and Classification #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and ELM #Social and Information Networks (cs.SI) #Stochastic Gradient Optimization Techniques
11. Hierarchical Optimal Transport for Multimodal Distribution Alignment
    2019/06/27 by John Lee, Max Dabagia, Lee, John +5 · 1 citation
    Computer Science · #Bayesian Methods and Mixture Models #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Text and Document Classification Technologies
12. Self-Expressive Decompositions for Matrix Approximation and Clustering
    2015/05/04 by Eva L. Dyer, Dyer, Eva L., Tom Goldstein +7 · 1 citation
    Computer Science · Engineering · Mathematics · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face and Expression Recognition #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Tensor decomposition and applications
13. LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration
    2023/08/28 by Ran Liu, Liu, Ran, Sahil Khose +11 · 1 citation
    Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning in Healthcare #Topic Modeling
14. Beyond Black Boxes: Enhancing Interpretability of Transformers Trained on Neural Data
    2025/06/16 by L. Michael Freeman, Philip Shamash, Freeman, Laurence +9 · 1 citation
    Computer Science · #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning #Neural Networks and Applications
15. Know Thyself by Knowing Others: Learning Neuron Identity from Population Context
    2025/12/01 by Vinam Arora, Divyansha Lachi, Arora, Vinam +13 · 1 citation
    Neuroscience · Biochemistry, Genetics and Molecular Biology · #Neural dynamics and brain function #Cell Image Analysis Techniques #EEG and Brain-Computer Interfaces