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Adrian Weller

23 papers at tracked venues · 20 at CORE A* · active 2024–2025

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Venues

ICLR ×9NeurIPS ×5ICML ×4EMNLP ×2AAAI ×1ACL ×1AISTATS ×1

Frequent coauthors

Isaac Reid
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Zeju Qiu
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Matthew Ashman
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Michalis Korakakis
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Matthew Wicker
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Stephan Rabanser
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Shoaib Ahmed Siddiqui
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Umang Bhatt
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Yanzhi Chen
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Top Piriyakulkij
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Yichao Liang
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Ali Shahin Shamsabadi
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Papers

  1. Can Large Language Models Understand Symbolic Graphics Programs?
    ICLR 2025 ·
    Zeju Qiu
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  2. Certification for Differentially Private Prediction in Gradient-Based Training
    ICML 2025 ·
    Matthew Wicker
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  3. Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
    ICML 2025 ·
    Stephan Rabanser
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  4. From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization
    NeurIPS 2025 ·
    Shoaib Ahmed Siddiqui
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  5. Gridded Transformer Neural Processes for Spatio-Temporal Data
    ICML 2025 ·
    Matthew Ashman
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  6. Learning Personalized Decision Support Policies
    AAAI 2025 ·
    Umang Bhatt
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  7. Linear Transformer Topological Masking with Graph Random Features
    ICLR 2025 ·
    Isaac Reid
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  8. Mitigating Shortcut Learning with InterpoLated Learning
    ACL 2025 ·
    Michalis Korakakis
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  9. Neural Mutual Information Estimation with Vector Copulas
    NeurIPS 2025 ·
    Yanzhi Chen
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  10. Orthogonal Finetuning Made Scalable
    EMNLP 2025 ·
    Zeju Qiu
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  11. PoE-World: Compositional World Modeling with Products of Programmatic Experts
    NeurIPS 2025 ·
    Top Piriyakulkij
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  12. Variance-Reducing Couplings for Random Features
    ICLR 2025 ·
    Isaac Reid
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  13. VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning
    ICLR 2025 ·
    Yichao Liang
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  14. ALVIN: Active Learning Via INterpolation
    EMNLP 2024 ·
    Michalis Korakakis
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  15. Approximately Equivariant Neural Processes
    NeurIPS 2024 ·
    Matthew Ashman
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  16. Confidential-DPproof: Confidential Proof of Differentially Private Training
    ICLR 2024 ·
    Ali Shahin Shamsabadi
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  17. Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024
    ICML 2024 ·
    Ruslan Salakhutdinov
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  18. General Graph Random Features
    ICLR 2024 ·
    Isaac Reid
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  19. Large Language Models Must Be Taught to Know What They Don't Know
    NeurIPS 2024 ·
    Sanyam Kapoor
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  20. Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers
    AISTATS 2024 ·
    Krzysztof Choromanski
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  21. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
    ICLR 2024 ·
    Longhui Yu
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  22. Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
    ICLR 2024 ·
    Weiyang Liu
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  23. Repelling Random Walks
    ICLR 2024 ·
    Isaac Reid
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