| 2025 | AAAI | Unlocking the Power of LSTM for Long Term Time Series Forecasting. | Yaxuan Kong, Zepu Wang, Yuqi Nie, Tian Zhou, Stefan Zohren, Yuxuan Liang, Peng Sun, Qingsong Wen |
| 2025 | ACL | Stories that (are) Move(d by) Markets: A Causal Exploration of Market Shocks and Semantic Shifts across Different Partisan Groups. | Felix Drinkall, Stefan Zohren, Michael McMahon, Janet B. Pierrehumbert |
| 2025 | ACL | Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement. | Yaxuan Kong, Yiyuan Yang, Yoontae Hwang, Wenjie Du, Stefan Zohren, Zhangyang Wang, Ming Jin, Qingsong Wen |
| 2025 | CIKM | Advances in Financial AI: Innovations, Risk, and Responsibility in the Era of LLMs. | Yongjae Lee, Nazanin Mehrasa, Chanyeol Choi, Chung-Chi Chen, Dhagash Mehta, Stefan Zohren, Yoon Kim, Chulheum Lee, Yeonhee Lee, Eunsook Oh |
| 2025 | COLING | Forecasting Credit Ratings: A Case Study where Traditional Methods Outperform Generative LLMs. | Felix Drinkall, Janet B. Pierrehumbert, Stefan Zohren |
| 2025 | ICML | LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data. | Peer Nagy, Sascha Yves Frey, Kang Li, Bidipta Sarkar, Svitlana Vyetrenko, Stefan Zohren, Ani Calinescu, Jakob Nicolaus Foerster |
| 2025 | KDD | The 11th Mining and Learning from Time Series (MILETS): From Classical Methods to LLMs. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Yuxuan Liang, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2024 | ECAI | Accelerating Machine Learning for Trading Using Programmable Switches. | Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman |
| 2024 | KDD | The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. | Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka |
| 2024 | NAACL | Time Machine GPT. | Felix Drinkall, Eghbal Rahimikia, Janet B. Pierrehumbert, Stefan Zohren |
| 2023 | HPSR | LOBIN: In-Network Machine Learning for Limit Order Books. | Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman |
| 2022 | AAAI | Same State, Different Task: Continual Reinforcement Learning without Interference. | Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts |
| 2022 | NAACL | Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts. | Felix Drinkall, Stefan Zohren, Janet B. Pierrehumbert |
| 2022 | SIGCOMM | Linnet: limit order books within switches. | Xinpeng Hong, Changgang Zheng, Stefan Zohren, Noa Zilberman |
| 2021 | MABS | Fast Agent-Based Simulation Framework with Applications to Reinforcement Learning and the Study of Trading Latency Effects. | Peter Belcak, Jan-Peter Calliess, Stefan Zohren |
| 2021 | UAI | Hierarchical Indian buffet neural networks for Bayesian continual learning. | Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen J. Roberts |
| 2020 | IJCNN | Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. | Bryan Lim, Stefan Zohren, Stephen Roberts |