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Showing papers from University College London, University of London Show all papers

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NeurIPS 2026University College London, UniveUniversity College LondonEvent sequences

From Jumps to Signatures: a Generative Method for Temporal Point Processes

Niels Cariou-Kotlarek, Vasileios Lampos

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ETHZ - ETH ZurichPoolside AIUniversity College London, UniveRL for LLMs

WATERFALL: Workflow for Adaptive Training with Evolutionary Reward Formulation and Automated Learning Loops

Eleftherios Triantafyllidis, Filippos Christianos, Zhibin Li, Bernd Bickel

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026NorthwesternUniversity College London, UniveDukeExploration

The Type Theory of Stationary MDPs: Rare Events and Uncertainty Quantification

Imon Banerjee, Sayak Chakrabarty, Ramkrishna Jyoti Samanta, Riddhiman Bhattacharya

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026SLAC National Accelerator LaboraUniversity College London, UniveTechnische Universität MünchenUCLHumboldt Universität BerlinPhysics-informed ML & PDEs

Neural Scaling Laws in Particle Jets

Matthias Vigl, Nikita Pond, Nicole Hartman, Jackson Barr and 10 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026OralU TübingenStanfordEberhard-Karls-Universität TübinTübingen AI Center, University oUniversity College London, UniveComputational neuroscience

Evaluating Neural Data Tokenizers: A Framework for Assessing Learned Representations of Spiking Activity

Federico D'Agostino, Alex Gilbert, Susanne Keller, Jaivardhan Kapoor and 16 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026King's College London, UnivUniversity College LondonUniversity College London, UniveSpeech synthesis

MFlowAudio: Efficient Text-to-Audio Synthesis via Mamba-based Stateful Flow Matching

Hao Dai, Panyu Chen, Jagmohan Chauhan

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Institute of automation, ChineseTsinghuaLi Auto Inc.University College London, UniveLi AutoOn-device ML

Dancing in Fetters: Pareto-Optimal On-Device LLMs under Hardware Constraints

Luoyang Sun, Jiwen Jiang, Yifeng Ding, Fengfa Li and 8 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U BristolU CambridgeRuprecht-Karls-Universität HeideU SouthamptonUniversity College London, UniveVideo-language models

The VLM as Sensor: Bayesian Active Search for Long Video Understanding

Chong Tang, Sannara EK, Dirk Koch, Robert Mullins and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026University College London, UniveGatsby Unit, UCLStanfordDeep learning theory

How are linear representations learned? Exact solutions to the dynamics of abstraction

William W Yang, Peter E Latham, Andrew Saxe

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Mohamed bin Zayed University of MBZUAIUniversity College London, UniveKnowledge distillation

SODA: Selective Optimization with Deferred BN Alignment for Efficient Dataset Distillation

Xinyue Bi, Jiacheng Cui, Yaxin Luo, Xinyi Shang and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Institute of cognitive neuroscieUniversity College LondonUniversity College London, UniveEmbodied agents

The limbic navigation system as a hierarchical RNN

Zilong Ji, Huiwen Zhang, Krishna Gorantla, Neil Burgess

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026University College London, UniveConcord AIStanfordEfficient & distributed training

An Analytical Model of Compute-limited Multistage Training Pipelines

Nishil Patel, Jin Hwa Lee, Basile Confavreux, Andrew Saxe

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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67%Highly rated
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NeurIPS 2026King's College London, UnivKing's College LondonUniversity College London, UniveClinical NLP & EHR

PULSE: Probabilistic Uncertainty-Aware Longitudinal Simulation for EHR Trajectories

Robert L Manschke, Angus Roberts, Julia Ive

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026King's College London, UnivThe Francis Crick InstituteUniversity College London, UniveExplainable AI

Concept frustration: Aligning human concepts and machine representations

A geometric framework defines concept frustration as contradictions from missing concepts and detects it in foundation model embeddings to align human and machine reasoning.

Christopher R. S. Banerji, Enrico Parisini, Christopher J Soelistyo, Ahab Isaac and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
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NeurIPS 2026University College LondonPenn StateGoogle Deepmind / UCLUniversity College London, UniveOptimization

Sobolev Regularized MMD Gradient Flow

Sobolev-regularized MMD gradient flow penalizes witness function gradients to ensure global convergence without isoperimetric assumptions, applying to both sampling and generative modeling.

Chenyang Tian, Bharath Sriperumbudur, Arthur Gretton, Zonghao Chen

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 2/5
medium 4/10
strict 3/5
71%Highly rated
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NeurIPS 2026The Chinese University of Hong KTsinghua Shenzhen International University College London, UniveUniversity College LondonNanjingUnified multimodal models

Meow-Omni 1: A Multimodal Large Language Model for Feline Ethology

Meow-Omni 1 integrates video, audio, physiological time-series, and text to reach 71.16% feline intent recognition, outperforming baseline multimodal models.

Jucheng Hu, Zhangquan Chen, Yulin Chen, Chengjie Hong and 8 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 3 on Hugging Face

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AI panel: 7 of 20 reviewers recommend it
lenient 3/5
medium 4/10
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71%Highly rated
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NeurIPS 2026The Hong Kong University of ScieHong Kong University of Science Hong Kong PolytechnicUniversity College London, Unive3D vision & reconstruction

UniGS: Unified Geometry-Aware Gaussian Splatting for Multimodal Rendering

UniGS proposes a unified geometry-aware Gaussian Splatting framework that simultaneously renders RGB, depth, normals, and semantics with state-of-the-art multimodal reconstruction accuracy.

Yusen XIE, Zhenmin Huang, Jianhao Jiao, Dimitrios Kanoulas and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 2/5
medium 3/10
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76%Highly rated
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NeurIPS 2026Gatsby Computational NeurosciencUniversity College London, UniveIST AustriaStanfordDeep learning theory

Optimal Representation Size: High-Dimensional Analysis of Pretraining and Linear Probing

High-dimensional analysis of pretraining via PCA and linear probing derives exact errors versus representation size, showing compression helps with abundant unlabeled but scarce labeled data.

Valentina Njaradi, Clémentine Dominé, Rachel A Swanson, Marco Mondelli and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 4/5
medium 4/10
strict 2/5
91%Must read
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NeurIPS 2026U OxfordU WashingtonUniversity College London, UnivePepperdineImperial College LondonAdversarial robustness

MedMisBench: Measuring Epistemic Resilience of LLMs Under Misleading Medical Context

MedMisBench reveals LLM medical accuracy collapses from 71% to 38% under misleading context, exposing a critical evaluation blind spot around epistemic resilience.

Hongjian Zhou, Xinyu Zou, Jinge Wu, Sean Wu and 18 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 4/5
80%Must read
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NeurIPS 2026UCLShanghai Jiao TongNanyang TechnologicalHarvardUniversity College London, UniveOffline RL

Fisher Decorator: Refining Flow Policy via A Local Transport Map

Fisher Decorator refines flow policies via local transport maps and Fisher-metric anisotropic optimization to fix isotropic approximation errors in offline RL.

Xiaoyuan Cheng, Haoyu Wang, Wenxuan Yuan, Ziyan Wang and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · Code ★ 26

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AI panel: 12 of 20 reviewers recommend it
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