Stefan Zohren - RankMe

89 papers A* 4A 3B 1C 2Journal 64Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	DeePM: Regime-Robust Deep Learning for Systematic Macro Portfolio Management. CoRR Kieran Wood, Stephen J. Roberts, Stefan Zohren
2026	J	`jnl`	Deep Learning for Financial Time Series: A Large-Scale Benchmark of Risk-Adjusted Performance. CoRR Adir Saly-Kaufmann, Kieran Wood, Jan-Peter Calliess, Stefan Zohren
2026	J	`jnl`	Evaluating LLMs in Finance Requires Explicit Bias Consideration. CoRR Yaxuan Kong, Hoyoung Lee, Yoontae Hwang, Alejandro Lopez-Lira, Bradford Levy, Dhagash Mehta, Qingsong Wen, Chanyeol Choi, Yongjae Lee, Stefan Zohren
2026	J	`jnl`	Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks. CoRR Kunihiro Miyazaki, Takanobu Kawahara, Stephen J. Roberts, Stefan Zohren
2025	A	`conf`	Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs. CIKM Yongjae Lee, Nazanin Mehrasa, Chanyeol Choi, Chung-Chi Chen, Dhagash Mehta, Stefan Zohren, Yoon Kim, Chulheum Lee, Yeonhee Lee, Eunsook Oh
2025	J	`jnl`	Decision-informed Neural Networks with Large Language Model Integration for Portfolio Optimization. CoRR Yoontae Hwang, Yaxuan Kong, Stefan Zohren, Yongjae Lee
2025	—	`conf`	Discrete Flow Matching is a Surprisingly Effective Post-training Method to Address Compound Error in Autoregressive Models. ICAIF Kang Li, Bidipta Sarkar, Zheng Xiong, Sascha Frey, Zilin Wang, Frensi Zejnullahu, Alfred Backhouse, Stefan Zohren, Anisoara Calinescu, Mihai Cucuringu, Jakob N. Foerster
2025	—	`conf`	Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative LLMs. COLING Workshops Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
2025	—	`conf`	Fusing Narrative Semantics for Financial Volatility Forecasting. ICAIF Yaxuan Kong, Yoontae Hwang, Marcus Kaiser, Chris Vryonides, Roel Oomen, Stefan Zohren
2025	J	`jnl`	Fusing Narrative Semantics for Financial Volatility Forecasting. CoRR Yaxuan Kong, Yoontae Hwang, Marcus Kaiser, Chris Vryonides, Roel Oomen, Stefan Zohren
2025	—	`conf`	JaxMARL-HFT: GPU-Accelerated Large-Scale Multi-Agent Reinforcement Learning for High-Frequency Trading. ICAIF Valentin Mohl, Sascha Frey, Reuben Leyland, Kang Li, George Nigmatulin, Mihai Cucuringu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu
2025	J	`jnl`	JaxMARL-HFT: GPU-Accelerated Large-Scale Multi-Agent Reinforcement Learning for High-Frequency Trading. CoRR Valentin Mohl, Sascha Frey, Reuben Leyland, Kang Li, George Nigmatulin, Mihai Cucuringu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu
2025	A*	`conf`	LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data. ICML Peer Nagy, Sascha Yves Frey, Kang Li, Bidipta Sarkar, Svitlana Vyetrenko, Stefan Zohren, Ani Calinescu, Jakob Nicolaus Foerster
2025	J	`jnl`	LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data. CoRR Peer Nagy, Sascha Frey, Kang Li, Bidipta Sarkar, Svitlana Vyetrenko, Stefan Zohren, Ani Calinescu, Jakob N. Foerster
2025	J	`jnl`	Position: Empowering Time Series Reasoning with Multimodal LLMs. CoRR Yaxuan Kong, Yiyuan Yang, Shiyu Wang, Chenghao Liu, Yuxuan Liang, Ming Jin, Stefan Zohren, Dan Pei, Yan Liu, Qingsong Wen
2025	J	`jnl`	Signature-Informed Transformer for Asset Allocation. CoRR Yoontae Hwang, Stefan Zohren
2025	—	`conf`	Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups. ACL (Findings) Felix Drinkall, Stefan Zohren, Michael McMahon, Janet B. Pierrehumbert
2025	J	`jnl`	Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups. CoRR Felix Drinkall, Stefan Zohren, Michael McMahon, Janet B. Pierrehumbert
2025	—	`conf`	The 11th Mining and Learning from Time Series (MILETS): From Classical Methods to LLMs. KDD (2) Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Yuxuan Liang, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka
2025	—	`conf`	Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement. ACL (1) Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, Wenjie Du, Stefan Zohren, Zhangyang Wang, Ming Jin, Qingsong Wen
2025	J	`jnl`	Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement. CoRR Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, Wenjie Du, Stefan Zohren, Zhangyang Wang, Ming Jin, Qingsong Wen
2025	J	`jnl`	Understanding stock market instability via graph auto-encoders. EPJ Data Sci. Dragos Gorduza, Stefan Zohren, Xiaowen Dong
2025	A*	`conf`	Unlocking the Power of LSTM for Long Term Time Series Forecasting. AAAI Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen
2025	J	`jnl`	When Dimensionality Hurts: The Role of LLM Embedding Compression for Noisy Regression Tasks. CoRR Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
2024	J	`jnl`	A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges. CoRR Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren
2024	A	`conf`	Accelerating Machine Learning for Trading Using Programmable Switches. ECAI Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman
2024	—	`conf`	Deep Learning for Options Trading: An End-To-End Approach. ICAIF Wee Ling Tan, Stephen Roberts, Stefan Zohren
2024	J	`jnl`	Deep Learning for Options Trading: An End-To-End Approach. CoRR Wee Ling Tan, Stephen J. Roberts, Stefan Zohren
2024	—	`conf`	Extracting Alpha from Financial Analyst Networks. ICAIF Dragos Gorduza, Yaxuan Kong, Xiaowen Dong, Stefan Zohren
2024	J	`jnl`	Temporal Representation Learning for Stock Similarities and Its Applications in Investment Management. CoRR Yoontae Hwang, Stefan Zohren, Yongjae Lee
2024	A*	`conf`	The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. KDD Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka
2024	—	`conf`	Time Machine GPT. NAACL-HLT (Findings) Felix Drinkall, Eghbal Rahimikia, Janet B. Pierrehumbert, Stefan Zohren
2024	J	`jnl`	Time Machine GPT. CoRR Felix Drinkall, Eghbal Rahimikia, Janet B. Pierrehumbert, Stefan Zohren
2024	J	`jnl`	Traditional Methods Outperform Generative LLMs at Forecasting Credit Ratings. CoRR Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren
2024	J	`jnl`	Unlocking the Power of LSTM for Long Term Time Series Forecasting. CoRR Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen
2023	J	`jnl`	Asynchronous Deep Double Dueling Q-learning for trading-signal execution in limit order book markets. Frontiers Artif. Intell. Peer Nagy, Jan-Peter Calliess, Stefan Zohren
2023	J	`jnl`	Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets. CoRR Peer Nagy, Jan-Peter Calliess, Stefan Zohren
2023	—	`conf`	Dynamic Time Warping for Lead-Lag Relationship Detection in Lagged Multi-Factor Models. ICAIF Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff, Stefan Zohren
2023	J	`jnl`	Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies. CoRR Kieran Wood, Samuel Kessler, Stephen J. Roberts, Stefan Zohren
2023	—	`conf`	Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network. ICAIF Peer Nagy, Sascha Frey, Silvia Sapora, Kang Li, Anisoara Calinescu, Stefan Zohren, Jakob N. Foerster
2023	J	`jnl`	Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network. CoRR Peer Nagy, Sascha Frey, Silvia Sapora, Kang Li, Anisoara Calinescu, Stefan Zohren, Jakob N. Foerster
2023	—	`conf`	JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading. ICAIF Sascha Yves Frey, Kang Li, Peer Nagy, Silvia Sapora, Christopher Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu
2023	J	`jnl`	JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading. CoRR Sascha Frey, Kang Li, Peer Nagy, Silvia Sapora, Chris Lu, Stefan Zohren, Jakob N. Foerster, Anisoara Calinescu
2023	C	`conf`	LOBIN: In-Network Machine Learning for Limit Order Books. HPSR Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman
2023	J	`jnl`	Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong
2023	J	`jnl`	Network Momentum across Asset Classes. CoRR Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren
2023	J	`jnl`	On Sequential Bayesian Inference for Continual Learning. CoRR Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts
2023	J	`jnl`	On Sequential Bayesian Inference for Continual Learning. Entropy Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts
2023	J	`jnl`	Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models. CoRR Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff, Stefan Zohren
2023	J	`jnl`	Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies. CoRR Wee Ling Tan, Stephen J. Roberts, Stefan Zohren
2022	J	`jnl`	DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions. CoRR Fernando Moreno-Pino, Stefan Zohren
2022	—	`conf`	Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts. NAACL-HLT Felix Drinkall, Stefan Zohren, Janet B. Pierrehumbert
2022	J	`jnl`	Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts. CoRR Felix Drinkall, Stefan Zohren, Janet B. Pierrehumbert
2022	J	`jnl`	Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training. J. Mach. Learn. Res. Diego Granziol, Stefan Zohren, Stephen Roberts
2022	—	`conf`	Linnet: limit order books within switches. SIGCOMM Posters and Demos Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman
2022	J	`jnl`	Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts
2022	A*	`conf`	Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
2022	J	`jnl`	Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity. CoRR Daniel Poh, Stephen J. Roberts, Stefan Zohren
2022	J	`jnl`	Understanding stock market instability via graph auto-encoders. CoRR Dragos Gorduza, Xiaowen Dong, Stefan Zohren
2021	J	`jnl`	Deep Learning for Market by Order Data. CoRR Zihao Zhang, Bryan Lim, Stefan Zohren
2021	J	`jnl`	Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures. CoRR Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts
2021	C	`conf`	Fast Agent-Based Simulation Framework with Applications to Reinforcement Learning and the Study of Trading Latency Effects. MABS Peter Belcak, Jan-Peter Calliess, Stefan Zohren
2021	A	`conf`	Hierarchical Indian buffet neural networks for Bayesian continual learning. UAI Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen J. Roberts
2021	J	`jnl`	Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units. CoRR Zihao Zhang, Stefan Zohren
2021	J	`jnl`	Realised Volatility Forecasting: Machine Learning via Financial Word Embedding. CoRR Eghbal Rahimikia, Stefan Zohren, Ser-Huang Poon
2021	J	`jnl`	Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts
2021	J	`jnl`	Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection. CoRR Kieran Wood, Stephen J. Roberts, Stefan Zohren
2021	J	`jnl`	Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture. CoRR Kieran Wood, Sven Giegerich, Stephen J. Roberts, Stefan Zohren
2020	J	`jnl`	Building Cross-Sectional Systematic Strategies By Learning to Rank. CoRR Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts
2020	J	`jnl`	Deep Learning for Portfolio Optimisation. CoRR Zihao Zhang, Stefan Zohren, Stephen Roberts
2020	J	`jnl`	Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio. CoRR Bryan Lim, Stefan Zohren, Stephen Roberts
2020	J	`jnl`	Fast Agent-Based Simulation Framework of Limit Order Books with Applications to Pro-Rata Markets and the Study of Latency Effects. CoRR Peter Belcak, Jan-Peter Calliess, Stefan Zohren
2020	J	`jnl`	Large Non-Stationary Noisy Covariance Matrices: A Cross-Validation Approach. CoRR Vincent W. C. Tan, Stefan Zohren
2020	J	`jnl`	Quantum Codes From Classical Graphical Models. IEEE Trans. Inf. Theory Joschka Roffe, Stefan Zohren, Dominic Horsman, Nicholas Chancellor
2020	B	`conf`	Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. IJCNN Bryan Lim, Stefan Zohren, Stephen Roberts
2020	J	`jnl`	Sentiment Diffusion in Financial News Networks and Associated Market Movements. CoRR Xingchen Wan, Jie Yang, Slavi Marinov, Jan-Peter Calliess, Stefan Zohren, Xiaowen Dong
2020	J	`jnl`	Time Series Forecasting With Deep Learning: A Survey. CoRR Bryan Lim, Stefan Zohren
2019	J	`jnl`	A Maximum Entropy approach to Massive Graph Spectra. CoRR Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	Deep Reinforcement Learning for Trading. CoRR Zihao Zhang, Stefan Zohren, Stephen J. Roberts
2019	J	`jnl`	DeepLOB: Deep Convolutional Neural Networks for Limit Order Books. IEEE Trans. Signal Process. Zihao Zhang, Stefan Zohren, Stephen J. Roberts
2019	J	`jnl`	Enhancing Time Series Momentum Strategies Using Deep Neural Networks. CoRR Bryan Lim, Stefan Zohren, Stephen J. Roberts
2019	J	`jnl`	Indian Buffet Neural Networks for Continual Learning. CoRR Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen Roberts
2019	J	`jnl`	MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs. CoRR Bryan Lim, Stefan Zohren, Stephen J. Roberts
2019	J	`jnl`	Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. CoRR Bryan Lim, Stefan Zohren, Stephen J. Roberts
2018	J	`jnl`	Entropic Spectral Learning in Large Scale Networks. CoRR Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2018	J	`jnl`	Gradient descent in Gaussian random fields as a toy model for high-dimensional optimisation in deep learning. CoRR Mariano Chouza, Stephen J. Roberts, Stefan Zohren
2018	J	`jnl`	Practical Bayesian Learning of Neural Networks via Adaptive Subgradient Methods. CoRR Arnold Salas, Stefan Zohren, Stephen J. Roberts