Daniel Beaglehole

20 papers A* 4Journal 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CAPYBARA: A generalizable framework for predicting serological measurements across human cohorts. PLoS Comput. Biol. Sierra Orsinelli-Rivers, Daniel Beaglehole, Tal Einav
2026	J	`jnl`	DANCE: Doubly Adaptive Neighborhood Conformal Estimation. CoRR Brandon R. Feng, Brian J. Reich, Daniel Beaglehole, Xihaier Luo, David Keetae Park, Shinjae Yoo, Zhechao Huang, Xueyu Mao, Olcay Boz, Jungeum Kim
2025	J	`jnl`	Aggregate and conquer: detecting and steering LLM concepts by combining nonlinear predictors over multiple layers. CoRR Daniel Beaglehole, Adityanarayanan Radhakrishnan, Enric Boix-Adserà, Mikhail Belkin
2025	A*	`conf`	Emergence in non-neural models: grokking modular arithmetic via average gradient outer product. ICML Neil Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin
2025	J	`jnl`	Steering Autoregressive Music Generation with Recursive Feature Machines. CoRR Daniel Zhao, Daniel Beaglehole, Taylor Berg-Kirkpatrick, Julian J. McAuley, Zachary Novack
2025	J	`jnl`	xRFM: Accurate, scalable, and interpretable feature learning models for tabular data. CoRR Daniel Beaglehole, David Holzmüller, Adityanarayanan Radhakrishnan, Mikhail Belkin
2024	A*	`conf`	Average gradient outer product as a mechanism for deep neural collapse. NeurIPS Daniel Beaglehole, Peter Súkeník, Marco Mondelli, Mikhail Belkin
2024	J	`jnl`	Average gradient outer product as a mechanism for deep neural collapse. CoRR Daniel Beaglehole, Peter Súkeník, Marco Mondelli, Mikhail Belkin
2024	J	`jnl`	Emergence in non-neural models: grokking modular arithmetic via average gradient outer product. CoRR Neil Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin
2024	J	`jnl`	Fast, optimal, and dynamic electoral campaign budgeting by a generalized Colonel Blotto game. CoRR Thomas Valles, Daniel Beaglehole
2024	J	`jnl`	Feature learning as alignment: a structural property of gradient descent in non-linear neural networks. Trans. Mach. Learn. Res. Daniel Beaglehole, Ioannis Mitliagkas, Atish Agarwala
2024	J	`jnl`	Gradient descent induces alignment between weights and the empirical NTK for deep non-linear networks. CoRR Daniel Beaglehole, Ioannis Mitliagkas, Atish Agarwala
2023	J	`jnl`	Mechanism of feature learning in convolutional neural networks. CoRR Daniel Beaglehole, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin
2023	J	`jnl`	On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions. SIAM J. Math. Data Sci. Daniel Beaglehole, Mikhail Belkin, Parthe Pandit
2023	A*	`conf`	Sampling Equilibria: Fast No-Regret Learning in Structured Games. SODA Daniel Beaglehole, Max Hopkins, Daniel Kane, Sihan Liu, Shachar Lovett
2022	J	`jnl`	An Efficient Approximation Algorithm for the Colonel Blotto Game. CoRR Daniel Beaglehole
2022	J	`jnl`	Feature learning in neural networks and kernel machines that recursively learn features. CoRR Adityanarayanan Radhakrishnan, Daniel Beaglehole, Parthe Pandit, Mikhail Belkin
2022	J	`jnl`	Kernel Ridgeless Regression is Inconsistent for Low Dimensions. CoRR Daniel Beaglehole, Mikhail Belkin, Parthe Pandit
2022	A*	`conf`	Learning to Hash Robustly, Guaranteed. ICML Alexandr Andoni, Daniel Beaglehole
2021	J	`jnl`	Learning to Hash Robustly, with Guarantees. CoRR Alexandr Andoni, Daniel Beaglehole