Alexander L. Gaunt

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 24

Top Topics

Top Venues

ICLR (Workshop)

Publications

Patrick Anderson, Erika Blancada Aranas, Youssef Assaf, Raphael Behrendt, Richard Black, Marco Caballero, Pashmina Cameron, Burcu Canakci, Thales De Carvalho, Andromachi Chatzieleftheriou, Rebekah Storan Clarke, James Clegg, Daniel Cletheroe, Bridgette Cooper, Tim Deegan, Austin Donnelly, Rokas Drevinskas, Alexander L. Gaunt, Christos Gkantsidis, Ariel Gomez Diaz, István Haller, Freddie Hong, Teodora Ilieva, Shashidhar Joshi, Russell Joyce, Mint Kunkel, David Lara, Sergey Legtchenko, Fanglin Linda Liu, Bruno Magalhães, Alana Marzoev, Marvin McNett, Jayashree Mohan, Michael Myrah, Trong Nguyen, Sebastian Nowozin, Aaron Ogus, Hiske Overweg, Antony I. T. Rowstron, Maneesh Sah, Masaaki Sakakura, Peter Scholtz, Nina Schreiner, Omer Sella, Adam Smith, Ioan A. Stefanovici, David Sweeney, Benn Thomsen, Govert Verkes, Phil Wainman, Jonathan Westcott, Luke Weston, Charles Whittaker, Pablo Wilke Berenguer, Hugh Williams, Thomas Winkler, Stefan Winzeck
Project Silica: Towards Sustainable Cloud Archival Storage in Glass. SOSP (2023)
Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose, James S. Spencer, Alexander L. Gaunt, James Kirkpatrick, Simon Axelrod, Peter W. Battaglia, Jonathan Godwin
Learned Force Fields Are Ready For Ground State Catalyst Discovery. CoRR (2022)
Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond. ICLR (2022)
Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt
Deterministic Variational Inference for Robust Bayesian Neural Networks. ICLR (2019)
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt
Learning to Represent Edits. ICLR (Poster) (2019)
Marc Brockschmidt, Miltiadis Allamanis, Alexander L. Gaunt, Oleksandr Polozov
Generative Code Modeling with Graphs. ICLR (Poster) (2019)
Marc Brockschmidt, Miltiadis Allamanis, Alexander L. Gaunt, Oleksandr Polozov
Generative Code Modeling with Graphs. CoRR (2018)
Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt
Constrained Graph Variational Autoencoders for Molecule Design. CoRR (2018)
Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel
Graph Partition Neural Networks for Semi-Supervised Classification. ICLR (Workshop) (2018)
Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt
Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks. CoRR (2018)
Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard S. Zemel
Graph Partition Neural Networks for Semi-Supervised Classification. CoRR (2018)
Patrick Anderson, Richard Black, Ausra Cerkauskaite, Andromachi Chatzieleftheriou, James Clegg, Chris Dainty, Raluca Diaconu, Rokas Drevinskas, Austin Donnelly, Alexander L. Gaunt, Andreas Georgiou, Ariel Gomez Diaz, Peter G. Kazansky, David Lara, Sergey Legtchenko, Sebastian Nowozin, Aaron Ogus, Douglas Phillips, Antony I. T. Rowstron, Masaaki Sakakura, Ioan A. Stefanovici, Benn Thomsen, Lei Wang, Hugh Williams, Mengyang Yang
Glass: A New Media for a New Era? HotStorage (2018)
Qi Liu, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt
Constrained Graph Variational Autoencoders for Molecule Design. NeurIPS (2018)
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander L. Gaunt
Learning to Represent Edits. CoRR (2018)
Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow
Lifelong Perceptual Programming By Example. ICLR (Workshop) (2017)
Chengtao Li, Daniel Tarlow, Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman
Neural Program Lattices. ICLR (Poster) (2017)
John K. Feser, Marc Brockschmidt, Alexander L. Gaunt, Daniel Tarlow
Neural Functional Programming. ICLR (Workshop) (2017)
Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow
Differentiable Programs with Neural Libraries. ICML (2017)
Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
DeepCoder: Learning to Write Programs. ICLR (Poster) (2017)
Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel Tarlow
Lifelong Perceptual Programming By Example. CoRR (2016)
John K. Feser, Marc Brockschmidt, Alexander L. Gaunt, Daniel Tarlow
Neural Functional Programming. CoRR (2016)
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, Daniel Tarlow
TerpreT: A Probabilistic Programming Language for Program Induction. CoRR (2016)
Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, Daniel Tarlow
DeepCoder: Learning to Write Programs. CoRR (2016)
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, Daniel Tarlow
Summary - TerpreT: A Probabilistic Programming Language for Program Induction. CoRR (2016)