On noncoherent correction of network errors and erasures with random locations. - Svitlana Vyetrenko; Tracey Ho; Elona Erez (ISIT, 2009)

Rate rRegions for coherent and noncoherent multisource network error correction. - Svitlana Vyetrenko; Tracey Ho; Michelle Effros; Jörg Kliewer; Elona Erez (ISIT, 2009)

Outer bounds on the error correction capacity region for non-multicast networks. - Svitlana Vyetrenko; Tracey Ho; Theodoros K. Dikaliotis (Allerton, 2010)

Erasure correction for nested receivers. - Ömer Faruk Tekin; Svitlana Vyetrenko; Tracey Ho; Hongyi Yao (Allerton, 2011)

Universal and robust distributed network codes. - Tracey Ho; Sidharth Jaggi; Svitlana Vyetrenko; Lingxiao Xia (INFOCOM, 2011)

Multiple-Access Network Information-Flow and Correction Codes. - Theodoros K. Dikaliotis; Tracey Ho; Sidharth Jaggi; Svitlana Vyetrenko; Hongyi Yao; Michelle Effros; Jörg Kliewer; Elona Erez (IEEE Trans. Inf. Theory, 2011)

Risk-Sensitive Compact Decision Trees for Autonomous Execution in Presence of Simulated Market Response. - Svitlana Vyetrenko; Shaojie Xu (CoRR, 2019)

Get real: realism metrics for robust limit order book market simulations. - Svitlana Vyetrenko; David Byrd; Nick Petosa; Mahmoud Mahfouz; Danial Dervovic; Manuela Veloso; Tucker Balch (ICAIF, 2020)

ABIDES-gym: gym environments for multi-agent discrete event simulation and application to financial markets. - Selim Amrouni; Aymeric Moulin; Jared Vann; Svitlana Vyetrenko; Tucker Balch; Manuela Veloso (ICAIF, 2021)

Towards realistic market simulations: a generative adversarial networks approach. - Andrea Coletta; Matteo Prata; Michele Conti; Emanuele Mercanti; Novella Bartolini; Aymeric Moulin; Svitlana Vyetrenko; Tucker Balch (ICAIF, 2021)

Profit equitably: an investigation of market maker's impact on equitable outcomes. - Kshama Dwarakanath; Svitlana S. Vyetrenko; Tucker Balch (ICAIF, 2021)

Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set. - Yuanlu Bai; Tucker Balch; Haoxian Chen 002; Danial Dervovic; Henry Lam; Svitlana Vyetrenko (CoRR, 2021)

Similarity metrics for Different Market Scenarios in Abides. - Diego Pino; Javier García 001; Fernando Fernández 001; Svitlana Vyetrenko (CoRR, 2021)

Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators. - Victor Storchan; Svitlana Vyetrenko; Tucker Balch (CoRR, 2021)

Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization. - Yuanlu Bai; Henry Lam; Svitlana Vyetrenko; Tucker Balch (CoRR, 2021)

Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization. - Yuanlu Bai; Henry Lam; Tucker Balch; Svitlana Vyetrenko (ICAIF, 2022)

Learning to simulate realistic limit order book markets from data as a World Agent. - Andrea Coletta; Aymeric Moulin; Svitlana Vyetrenko; Tucker Balch (ICAIF, 2022)

Optimal Stopping with Gaussian Processes. - Kshama Dwarakanath; Danial Dervovic; Peyman Tavallali; Svitlana Vyetrenko; Tucker Balch (ICAIF, 2022)

Equitable Marketplace Mechanism Design. - Kshama Dwarakanath; Svitlana Vyetrenko; Tucker Balch (ICAIF, 2022)

StyleTime: Style Transfer for Synthetic Time Series Generation. - Yousef El-Laham; Svitlana Vyetrenko (ICAIF, 2022)

HyperTime: Implicit Neural Representation for Time Series. - Elizabeth Fons; Alejandro Sztrajman; Yousef El-Laham; Alexandros Iosifidis; Svitlana Vyetrenko (CoRR, 2022)

Biased or Limited: Modeling Sub-Rational Human Investors in Financial Markets. - Penghang Liu; Kshama Dwarakanath; Svitlana S. Vyetrenko (CoRR, 2022)

DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift. - Defu Cao; Yousef El-Laham; Loc Trinh; Svitlana Vyetrenko; Yan Liu 002 (CoRR, 2022)

Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections. - Tom Bamford; Andrea Coletta; Elizabeth Fons; Sriram Gopalakrishnan; Svitlana Vyetrenko; Tucker Balch; Manuela Veloso (ICAIF, 2023)

Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness. - Andrea Coletta; Joseph Jerome; Rahul Savani; Svitlana Vyetrenko (ICAIF, 2023)

On Correlated Stock Market Time Series Generation. - Giuseppe Masi; Matteo Prata; Michele Conti; Novella Bartolini; Svitlana Vyetrenko (ICAIF, 2023)

Stock Shocks Modelling and Forecasting. - Viviana Arrigoni; Giuseppe Masi; Emanuele Mercanti; Novella Bartolini; Svitlana Vyetrenko (ICDCS Workshops, 2023)

K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs. - Andrea Coletta; Svitlana Vyetrenko; Tucker Balch (ICML, 2023)

On the Constrained Time-Series Generation Problem. - Andrea Coletta; Sriram Gopalakrishnan; Daniel Borrajo; Svitlana Vyetrenko (NeurIPS, 2023)

Deep Gaussian mixture ensembles. - Yousef El-Laham; Niccolò Dalmasso; Elizabeth Fons; Svitlana Vyetrenko (UAI, 2023)

Transparency As Delayed Observability In Multi-Agent Systems. - Kshama Dwarakanath; Svitlana Vyetrenko; Tucker Balch; Toks Oyebode (WSC, 2023)

Once burned, twice shy? The effect of stock market bubbles on traders that learn by experience. - Haibei Zhu; Svitlana Vyetrenko; Kshama Dwarakanath; Tucker Balch; Serafin Grundl; David Byrd (WSC, 2023)

K-SHAP: Policy Clustering Algorithm for Anonymous State-Action Pairs. - Andrea Coletta; Svitlana Vyetrenko; Tucker Balch (CoRR, 2023)

MADS: Modulated Auto-Decoding SIREN for time series imputation. - Tom Bamford; Elizabeth Fons; Yousef El-Laham; Svitlana Vyetrenko (CoRR, 2023)

ATMS: Algorithmic Trading-Guided Market Simulation. - Song Wei; Andrea Coletta; Svitlana Vyetrenko; Tucker Balch (CoRR, 2023)

A Model-Based Synthetic Stock Price Time Series Generation Framework. - Haibei Zhu; Svitlana Vyetrenko; Tucker Balch (CoRR, 2023)

Analyzing the Impact of Tax Credits on Households in Simulated Economic Systems with Learning Agents. - Jialin Dong; Kshama Dwarakanath; Svitlana Vyetrenko (CoRR, 2023)

Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmark. - Elizabeth Fons; Rachneet Kaur; Soham Palande; Zhen Zeng; Tucker Balch; Manuela Veloso; Svitlana Vyetrenko (EMNLP, 2024)

Tax Credits and Household Behavior: The Roles of Myopic Decision-Making and Liquidity in a Simulated Economy. - Kshama Dwarakanath; Jialin Dong; Svitlana Vyetrenko (ICAIF, 2024)

TADACap: Time-series Adaptive Domain-Aware Captioning. - Elizabeth Fons; Rachneet Kaur; Zhen Zeng; Soham Palande; Tucker Balch; Svitlana Vyetrenko; Manuela Veloso (ICAIF, 2024)

Augment on Manifold: Mixup Regularization with UMAP. - Yousef El-Laham; Elizabeth Fons; Dillon Daudert; Svitlana Vyetrenko (ICASSP, 2024)

Neural Stochastic Differential Equations with Change Points: A Generative Adversarial Approach. - Zhongchang Sun; Yousef El-Laham; Svitlana Vyetrenko (ICASSP, 2024)

Synthetic Data Applications in Finance. - Vamsi K. Potluru; Daniel Borrajo; Andrea Coletta; Niccolò Dalmasso; Yousef El-Laham; Elizabeth Fons; Mohsen Ghassemi; Sriram Gopalakrishnan; Vikesh Gosai; Eleonora Kreacic; Ganapathy Mani; Saheed Obitayo; et al. (CoRR, 2024)

LLM-driven Imitation of Subrational Behavior : Illusion or Reality? - Andrea Coletta; Kshama Dwarakanath; Penghang Liu; Svitlana Vyetrenko; Tucker Balch (CoRR, 2024)

ABIDES-Economist: Agent-Based Simulation of Economic Systems with Learning Agents. - Kshama Dwarakanath; Svitlana Vyetrenko; Peyman Tavallali; Tucker Balch (CoRR, 2024)

Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmark. - Elizabeth Fons; Rachneet Kaur; Soham Palande; Zhen Zeng; Svitlana Vyetrenko; Tucker Balch (CoRR, 2024)

A Language Model-Guided Framework for Mining Time Series with Distributional Shifts. - Haibei Zhu; Yousef El-Laham; Elizabeth Fons; Svitlana Vyetrenko (CoRR, 2024)

Empirical Equilibria in Agent-based Economic systems with Learning agents. - Kshama Dwarakanath; Svitlana Vyetrenko; Tucker Balch (CoRR, 2024)

iHyperTime: Interpretable Time Series Generation with Implicit Neural Representations. - Elizabeth Fons; Alejandro Sztrajman; Yousef El-Laham; Andrea Coletta; Alexandros Iosifidis; Svitlana Vyetrenko (Trans. Mach. Learn. Res., 2024)

Lob-based deep learning models for stock price trend prediction: a benchmark study. - Matteo Prata; Giuseppe Masi; Leonardo Berti; Viviana Arrigoni; Andrea Coletta; Irene Cannistraci; Svitlana Vyetrenko; Paola Velardi; Novella Bartolini (Artif. Intell. Rev., 2024)

Mixup Regularization: A Probabilistic Perspective. - Yousef El-Laham; Niccolò Dalmasso; Svitlana Vyetrenko; Vamsi K. Potluru; Manuela Veloso (UAI, 2025)

Variational Neural Stochastic Differential Equations with Change Points. - Yousef El-Laham; Zhongchang Sun; Haibei Zhu; Tucker Balch; Svitlana Vyetrenko (Trans. Mach. Learn. Res., 2025)

LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data. - Peer Nagy; Sascha Frey; Kang Li; Bidipta Sarkar; Svitlana Vyetrenko; Stefan Zohren; Ani Calinescu; Jakob N. Foerster (CoRR, 2025)

LSCD: Lomb-Scargle Conditioned Diffusion for Time series Imputation. - Elizabeth Fons; Alejandro Sztrajman; Yousef El-Laham; Luciana Ferrer; Svitlana Vyetrenko; Manuela Veloso (CoRR, 2025)

AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation. - Elizabeth Fons; Elena Kochkina; Rachneet Kaur; Zhen Zeng; Berowne Hlavaty; Charese Smiley; Svitlana Vyetrenko; Manuela Veloso (CoRR, 2025)

Towards Interpretable Time Series Foundation Models. - Matthieu Boileau; Philippe Helluy; Jeremy Pawlus; Svitlana Vyetrenko (CoRR, 2025)

Time-RA: Towards Time Series Reasoning for Anomaly with LLM Feedback. - Yiyuan Yang; Zichuan Liu; Lei Song; Kai Ying; Zhiguang Wang; Tom Bamford; Svitlana Vyetrenko; Jiang Bian 001; Qingsong Wen (CoRR, 2025)