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Alex Beatson

7 papers · 2016–2021 · 3 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+1 more ↓ 🌍 Conference Polyglot Β· Bronze πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze πŸ—ΊοΈ Taxonomy Completionist (15) 🐣 Hot Topic Early Bird
πŸ‘‘ Triple Crown

Venues

ICLR (3) ICML (2) NeurIPS (2)

Top co-authors

Ryan P. Adams (2) Ryan P Adams (2) Tianju Xue (2) Zhaoran Wang (1) Jordan Ash (1) Deniz Oktay (1) David Duvenaud (1) Mohammad Norouzi (1) Han Liu (1) Ricky T. Q. Chen (1)

Research topics

Machine Learning (7) Optimization & Theory (6) Deep Learning (4) Application Areas (3) Artificial Intelligence (2) Mathematics & Optimization (2) Architectures (2) Learning Paradigms (2) Learning Types (2) Optimization (2) Core Methods (1) Mathematics (1) Models (1) Techniques (1)

Keywords

variational inference (3) finite element analysis (2) potential energy (2) neural network (2) automatic differentiation (1) gradient estimation (1) parametric optimization (1) amortized inference (1) minimax risk (1) latent variable model (1) convergence rate (1) recurrent neural network (1) memory efficiency (1) partial differential equation (1) gradient estimator (1) unbiased estimation (1) surrogate modeling (1) robust estimator (1) unbiased gradient (1) pde-constrained optimization (1)

Papers

Randomized Automatic Differentiation ICLR 2021 Amortized Finite Element Analysis for Fast PDE-Constrained Optimization ICML 2020 Learning Composable Energy Surrogates for PDE Order Reduction NeurIPS 2020 SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models ICLR 2020 Amortized Bayesian Meta-Learning ICLR 2019 Efficient optimization of loops and limits with randomized telescoping sums ICML 2019 Blind Attacks on Machine Learners NeurIPS 2016