Symmetry-Breaking Bifurcation in Nonlinear Schrödinger/Gross-Pitaevskii Equations. - E. W. Kirr; P. G. Kevrekidis; Eli Shlizerman; Michael I. Weinstein (SIAM J. Math. Anal., 2008)

Neural Dynamics, Bifurcations, and Firing Rates in a Quadratic Integrate-and-Fire Model with a Recovery Variable. I: Deterministic Behavior. - Eli Shlizerman; Philip Holmes (Neural Comput., 2012)

The Low Dimensionality of Time-Periodic Standing Waves in Water of Finite and Infinite Depth. - Matthew O. Williams; Eli Shlizerman; Jon Wilkening; J. Nathan Kutz (SIAM J. Appl. Dyn. Syst., 2012)

Neural Activity Measures and Their Dynamics. - Eli Shlizerman; Konrad Schroder; J. Nathan Kutz (SIAM J. Appl. Math., 2012)

Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe. - Eli Shlizerman; Jeffrey Riffell; J. Nathan Kutz (Frontiers Comput. Neurosci., 2014)

Multistability and Long-Timescale Transients Encoded by Network Structure in a Model of C. elegans Connectome Dynamics. - James M. Kunert-Graf; Eli Shlizerman; Andrew Walker; J. Nathan Kutz (Frontiers Comput. Neurosci., 2017)

Classification of Fixed Point Network Dynamics from Multiple Node Timeseries Data. - David Blaszka; Elischa Sanders; Jeffrey Riffell; Eli Shlizerman (Frontiers Neuroinformatics, 2017)

Audio to Body Dynamics. - Eli Shlizerman; Lucio M. Dery; Hayden Schoen; Ira Kemelmacher-Shlizerman (CVPR, 2018)

An Optical Frontend for a Convolutional Neural Network. - Shane Colburn; Yi Chu; Eli Shlizerman; Arka Majumdar (CoRR, 2019)

Dimension Reduction Approach for Interpretability of Sequence to Sequence Recurrent Neural Networks. - Kun Su; Eli Shlizerman (CoRR, 2019)

Neural Interactome: Interactive Simulation of a Neuronal System. - Jimin Kim; William Leahy; Eli Shlizerman (Frontiers Comput. Neurosci., 2019)

PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition. - Kun Su; Xiulong Liu; Eli Shlizerman (CVPR, 2020)

Audeo: Audio Generation for a Silent Performance Video. - Kun Su; Xiulong Liu; Eli Shlizerman (NeurIPS, 2020)

R-FORCE: Robust Learning for Random Recurrent Neural Networks. - Yang Zheng; Eli Shlizerman (CoRR, 2020)

Iterate & Cluster: Iterative Semi-Supervised Action Recognition. - Jingyuan Li; Eli Shlizerman (CoRR, 2020)

Deep Reinforcement Learning for Neural Control. - Jimin Kim; Eli Shlizerman (CoRR, 2020)

BI-MAML: Balanced Incremental Approach for Meta Learning. - Yang Zheng; Jinlin Xiang; Kun Su; Eli Shlizerman (CoRR, 2020)

Sparse Semi-Supervised Action Recognition with Active Learning. - Jingyuan Li; Eli Shlizerman (CoRR, 2020)

Multi-Instrumentalist Net: Unsupervised Generation of Music from Body Movements. - Kun Su; Xiulong Liu; Eli Shlizerman (CoRR, 2020)

Clustering and Recognition of Spatiotemporal Features Through Interpretable Embedding of Sequence to Sequence Recurrent Neural Networks. - Kun Su; Eli Shlizerman (Frontiers Artif. Intell., 2020)

How Does it Sound? - Kun Su; Xiulong Liu; Eli Shlizerman (NeurIPS, 2021)

Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks. - Jinlin Xiang; Shane Colburn; Arka Majumdar; Eli Shlizerman (CoRR, 2021)

STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers. - Trung Le 002; Eli Shlizerman (NeurIPS, 2022)

INRAS: Implicit Neural Representation for Audio Scenes. - Kun Su; Mingfei Chen; Eli Shlizerman (NeurIPS, 2022)

Lyapunov-Guided Embedding for Hyperparameter Selection in Recurrent Neural Networks. - Ryan Vogt; Yang Zheng; Eli Shlizerman (CoRR, 2022)

STNDT: Modeling Neural Population Activity with a Spatiotemporal Transformer. - Trung Le 002; Eli Shlizerman (CoRR, 2022)

TKIL: Tangent Kernel Approach for Class Balanced Incremental Learning. - Jinlin Xiang; Eli Shlizerman (CoRR, 2022)

On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools. - Ryan Vogt; Maximilian Puelma Touzel; Eli Shlizerman; Guillaume Lajoie (Frontiers Appl. Math. Stat., 2022)

Statistical perspective on functional and causal neural connectomics: The Time-Aware PC algorithm. - Rahul Biswas; Eli Shlizerman (PLoS Comput. Biol., 2022)

Physics-Driven Diffusion Models for Impact Sound Synthesis from Videos. - Kun Su; Kaizhi Qian; Eli Shlizerman; Antonio Torralba 001; Chuang Gan 001 (CVPR, 2023)

Be Everywhere - Hear Everything (BEE): Audio Scene Reconstruction by Sparse Audio-Visual Samples. - Mingfei Chen; Kun Su; Eli Shlizerman (ICCV, 2023)

TKIL: Tangent Kernel Optimization for Class Balanced Incremental Learning. - Jinlin Xiang; Eli Shlizerman (ICCV (Workshops), 2023)

AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity. - Jingyuan Li; Leo Scholl; Trung Le 002; Pavithra Rajeswaran; Amy L. Orsborn; Eli Shlizerman (NeurIPS, 2023)

Learning Time-Invariant Representations for Individual Neurons from Population Dynamics. - Lu Mi; Trung Le 002; Tianxing He; Eli Shlizerman; Uygar Sümbül (NeurIPS, 2023)

Comparison of Deep Learning and Signal Processing Methods for Removing a Ringing Artifact from Ultrasound Signals. - Yana Sosnovskaya; Eli Shlizerman; Blake Hannaford; Mika N. Sinanan (SAS, 2023)

Evolutionary algorithms as an alternative to backpropagation for supervised training of Biophysical Neural Networks and Neural ODEs. - James Hazelden; Yuhan Helena Liu; Eli Shlizerman; Eric Shea-Brown (CoRR, 2023)

Dataset for monkeys A and B from AMAG: Additive, Multiplicative and Adaptive Graph Neural Network For Forecasting Neuron Activity. - Jingyuan Li; Leo Scholl; Trung Le 002; Pavithra Rajeswaran; Amy L. Orsborn; Eli Shlizerman (Zenodo, 2023)

From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation. - Kun Su; Xiulong Liu; Eli Shlizerman (ICML, 2024)

AV-Cloud: Spatial Audio Rendering Through Audio-Visual Cloud Splatting. - Mingfei Chen; Eli Shlizerman (NeurIPS, 2024)

Tell What You Hear From What You See - Video to Audio Generation Through Text. - Xiulong Liu; Kun Su; Eli Shlizerman (NeurIPS, 2024)

Let the Beat Follow You - Creating Interactive Drum Sounds From Body Rhythm. - Xiulong Liu; Kun Su; Eli Shlizerman (WACV, 2024)

Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation. - Qibin Liu; Chase Shimmin; Xiulong Liu; Eli Shlizerman; Shu Li; Shih-Chieh Hsu (CoRR, 2024)

Compressed Meta-Optical Encoder for Image Classification. - Anna Wirth-Singh; Jinlin Xiang; Minho Choi 001; Johannes E. Fröch; Luocheng Huang; Shane Colburn; Eli Shlizerman; Arka Majumdar (CoRR, 2024)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation. - Claudius Krause; Michele Faucci Giannelli; Gregor Kasieczka; Benjamin Nachman; Dalila Salamani; David Shih; Anna Zaborowska; Oz Amram; Kerstin Borras; Matthew R. Buckley; Erik Buhmann; Thorsten Buss; et al. (CoRR, 2024)

Transferable polychromatic optical encoder for neural networks. - Minho Choi 001; Jinlin Xiang; Anna Wirth-Singh; Seung-Hwan Baek; Eli Shlizerman; Arka Majumdar (CoRR, 2024)

Brain-to-Text Benchmark '24: Lessons Learned. - Francis R. Willett; Jingyuan Li; Trung Le 002; Chaofei Fan; Mingfei Chen; Eli Shlizerman; Yue Chen; Xin Zheng; Tatsuo S. Okubo; Tyler Benster; Hyun Dong Lee; Maxwell Kounga; et al. (CoRR, 2024)

AL-SAR: Active Learning for Skeleton-Based Action Recognition. - Jingyuan Li; Trung Le 002; Eli Shlizerman (IEEE Trans. Neural Networks Learn. Syst., 2024)

Lyapunov-guided representation of recurrent neural network performance. - Ryan Vogt; Yang Zheng; Eli Shlizerman (Neural Comput. Appl., 2024)

Correction: Lyapunov-guided representation of recurrent neural network performance. - Ryan Vogt; Yang Zheng; Eli Shlizerman (Neural Comput. Appl., 2024)

SoundVista: Novel-View Ambient Sound Synthesis via Visual-Acoustic Binding. - Mingfei Chen; Israel D. Gebru; Ishwarya Ananthabhotla; Christian Richardt; Dejan Markovic; Jake Sandakly; Steven Krenn; Todd Keebler; Eli Shlizerman; Alexander Richard (CVPR, 2025)

Hearing Anywhere in Any Environment. - Xiulong Liu; Anurag Kumar 003; Paul Calamia; Sebastià Vicenc Amengual Garí; Calvin Murdock; Ishwarya Ananthabhotla; Philip W. Robinson; Eli Shlizerman; Vamsi Krishna Ithapu; Ruohan Gao (CVPR, 2025)

IGSM: Improved Geometric and Sensitivity Matching for Finetuning Pruned Diffusion Models. - Caleb Zheng; Eli Shlizerman (CoRR, 2025)

SAVVY: Spatial Awareness via Audio-Visual LLMs through Seeing and Hearing. - Mingfei Chen; Zijun Cui; Xiulong Liu; Jinlin Xiang; Caleb Zheng; Jingyuan Li; Eli Shlizerman (CoRR, 2025)

Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum. - Caleb Zheng; Eli Shlizerman (CoRR, 2025)

KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks. - James Hazelden; Laura Driscoll; Eli Shlizerman; Eric Shea-Brown (CoRR, 2025)

SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding. - Trung Le 002; Hao Fang; Jingyuan Li; Tung Nguyen; Lu Mi; Amy L. Orsborn; Uygar Sümbül; Eli Shlizerman (CoRR, 2025)

Neural Tangent Knowledge Distillation for Optical Convolutional Networks. - Jinlin Xiang; Minho Choi 001; Yubo Zhang; Zhihao Zhou; Arka Majumdar; Eli Shlizerman (CoRR, 2025)