Feng Chen
Professor
Works on brain-inspired computing, machine learning, probabilistic graphical models, computer vision, and video analysis.
Feng Chen's lab at Tsinghua works on video understanding and probabilistic & causal inference. 16 papers since 2023, 7 at top venues, mostly ICML and Neurocomputing. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 44%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 7 papers2025 · T1 3
- 3 papers2024 · T1 2
- 4 papers2023 · T1 2
T1 venuesOtherVenues: ICML, Neurocomputing, AAAI, Findings of EMNLP, ICCV
Research focuspaper titles that use each topic's words
- Probabilistic & causal inference2 papers
- Video understanding1 paper
- graphical models0 papers
- graphical0 papers
- video analysis0 papers
Paper list
From DBLP.
20262 papers
- IEEE Trans. Neural Networks Learn. Syst.Chain-of-Detection: Enhancing Cross-Granularity Robotic Perception for Object Manipulation (opens in a new tab)
- Trans. Mach. Learn. Res.Reconciling In-Context and In-Weight Learning via Dual Representation Space Encoding (opens in a new tab)
20257 papers
- NeurIPS (T1)Adaptive Fission: Post-training Encoding for Low-latency Spike Neural Networks (opens in a new tab)
- NeurocomputingCausal dreamer for partially observable model-based reinforcement learning (opens in a new tab)
- Findings of EMNLPExploring the Hidden Reasoning Process of Large Language Models by Misleading Them (opens in a new tab)
- NeurocomputingIterative compression towards in-distribution features in domain generalization (opens in a new tab)
- Mach. Vis. Appl.Multi-core token mixer: a novel approach for underwater image enhancement (opens in a new tab)
- ICCV (T1)OURO: A Self-Bootstrapped Framework for Enhancing Multimodal Scene Understanding (opens in a new tab)
- ICML (T1)When do neural networks learn world models? (opens in a new tab)
20243 papers
- ICML (T1)Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize (opens in a new tab)
- Trans. Mach. Learn. Res.M3PL: Identifying and Exploiting View Bias of Prompt Learning (opens in a new tab)
- ICLR (T1)Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers (opens in a new tab)
20234 papers
- TPAMI (T1)Adjacency Constraint for Efficient Hierarchical Reinforcement Learning (opens in a new tab)
- AAAI (T1)Fast Counterfactual Inference for History-Based Reinforcement Learning (opens in a new tab)
- Knowl. Based Syst.MER: Modular Element Randomization for robust generalizable policy in deep reinforcement learning (opens in a new tab)
- IEEE Trans. Neural Networks Learn. Syst.Partial Consistency for Stabilizing Undiscounted Reinforcement Learning (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to TsinghuaFall 2027
Computer Science PhD (international applicants)
- Round
- Main
- Opens
- GRE
- See program page
- English
- Per school catalog
- Fee
- RMB 800
Not yet confirmed for this intake.
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Your notes
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Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- DBLP
- Members
- Not collected
- Alumni
- Not collected
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