Kyle Mills

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All published works

Action	Title	Year	Authors
+ PDF Chat	Optimizing thermodynamic trajectories using evolutionary and gradient-based reinforcement learning	2021	Chris Beeler Uladzimir Yahorau Rory Coles Kyle Mills Stephen Whitelam Isaac Tamblyn
+ PDF Chat	Optical lattice experiments at unobserved conditions with generative adversarial deep learning	2021	Corneel Casert Kyle Mills Tom Vieijra J. Ryckebusch Isaac Tamblyn
+	Weakly-supervised multi-class object localization using only object counts as labels	2021	Kyle Mills Isaac Tamblyn
+ PDF Chat	Finding the ground state of spin Hamiltonians with reinforcement learning	2020	Kyle Mills Pooya Ronagh Isaac Tamblyn
+ PDF Chat	Controlled Online Optimization Learning (COOL): Finding the ground state of spin Hamiltonians with reinforcement learning	2020	Kyle Mills Pooya Ronagh Isaac Tamblyn
+	Optimizing thermodynamic trajectories using evolutionary reinforcement learning.	2019	Chris Beeler Uladzimir Yahorau Rory Coles Kyle Mills Stephen Whitelam Isaac Tamblyn
+ PDF Chat	Extensive deep neural networks for transferring small scale learning to large scale systems	2019	Kyle Mills Kevin Ryczko Iryna Luchak Adam Domurad Chris Beeler Isaac Tamblyn
+ PDF Chat	Deep neural networks for direct, featureless learning through observation: The case of two-dimensional spin models	2018	Kyle Mills Isaac Tamblyn
+ PDF Chat	Convolutional neural networks for atomistic systems	2018	Kevin Ryczko Kyle Mills Iryna Luchak Christa M. Homenick Isaac Tamblyn
+ PDF Chat	Deep learning and the Schrödinger equation	2017	Kyle Mills Michael Spanner Isaac Tamblyn
+	Extensive deep neural networks	2017	Iryna Luchak Kyle Mills Kevin Ryczko Adam Domurad Isaac Tamblyn
+	Deep learning and the Schrödinger equation	2017	Kyle Mills Michael Spanner Isaac Tamblyn
+	Phase space sampling and operator confidence with generative adversarial networks	2017	Kyle Mills Isaac Tamblyn

Common Coauthors

Coauthor	Papers Together
Isaac Tamblyn	13
Chris Beeler	3
Iryna Luchak	3
Kevin Ryczko	3
Michael Spanner	2
Rory Coles	2
Adam Domurad	2
Stephen Whitelam	2
Pooya Ronagh	2
Christa M. Homenick	1
Tom Vieijra	1
Uladzimir Yahorau	1
Corneel Casert	1
J. Ryckebusch	1
Uladzimir Yahorau	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Solving the quantum many-body problem with artificial neural networks	2017	Giuseppe Carleo Matthias Troyer	4
+ PDF Chat	Deep learning and the Schrödinger equation	2017	Kyle Mills Michael Spanner Isaac Tamblyn	4
+ PDF Chat	Machine learning for many-body physics: The case of the Anderson impurity model	2014	Louis-François Arsenault Alejandro López‐Bezanilla O. Anatole von Lilienfeld Andrew J. Millis	3
+ PDF Chat	Quantum-chemical insights from deep tensor neural networks	2017	Kristof T. Schütt Farhad Arbabzadah Stefan Chmiela K. Müller Alexandre Tkatchenko	3
+ PDF Chat	Learning phase transitions by confusion	2017	Evert van Nieuwenburg Ye-Hua Liu Sebastian D. Huber	3
+	Bounded and Inhomogeneous Ising Models. I. Specific-Heat Anomaly of a Finite Lattice	1969	Arthur E. Ferdinand Michael E. Fisher	3
+ PDF Chat	Machine learning phases of matter	2017	Juan Carrasquilla Roger G. Melko	3
+ PDF Chat	Application of Quantum Annealing to Nurse Scheduling Problem	2019	Kazuki Ikeda Y. Nakamura Travis S. Humble	2
+	TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems	2016	Martı́n Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Gregory S. Corrado Andy Davis Jay B. Dean Matthieu Devin	2
+ PDF Chat	Solving the graph-isomorphism problem with a quantum annealer	2012	Itay Hen A. P. Young	2
+ PDF Chat	Ising formulations of many NP problems	2014	Andrew Lucas	2
+ PDF Chat	On representing chemical environments	2013	Albert P. Bartók Risi Kondor Gábor Cśanyi	2
+ PDF Chat	Efficient, Multiple-Range Random Walk Algorithm to Calculate the Density of States	2001	Fugao Wang D. P. Landau	2
+ PDF Chat	Kinetic Energy of Hydrocarbons as a Function of Electron Density and Convolutional Neural Networks	2016	Kun Yao John Parkhill	2
+ PDF Chat	Machine Learning Phases of Strongly Correlated Fermions	2017	Kelvin Ch’ng Juan Carrasquilla Roger G. Melko Ehsan Khatami	2
+	Quantum annealing: A new method for minimizing multidimensional functions	1994	Aleta Finnila Maria A. Gomez C. Sebenik C. Stenson J. D. Doll	2
+ PDF Chat	Quantum versus classical annealing of Ising spin glasses	2015	Bettina Heim Troels F. Rønnow Sergei V. Isakov Matthias Troyer	2
+ PDF Chat	Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer	2019	Maliheh Aramon Gili Rosenberg E. Valiante Toshiyuki Miyazawa Hirotaka Tamura Helmut G. Katzgraber	2
+ PDF Chat	Understanding machine‐learned density functionals	2015	Li Li John Snyder Isabelle M. Pelaschier Jessica Huang Uma‐Naresh Niranjan Paul Duncan Matthias Rupp Klaus‐Robert Müller Kieron Burke	2
+	Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules	2018	Rafael Gómez‐Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla Jorge Aguilera‐Iparraguirre Timothy Hirzel Ryan P. Adams Alán Aspuru‐Guzik	2
+ PDF Chat	Bypassing the Kohn-Sham equations with machine learning	2017	Felix Brockherde Leslie Vogt-Maranto Li Li Mark E. Tuckerman Kieron Burke Klaus‐Robert Müller	2
+	Annealing by simulating the coherent Ising machine	2019	Egor Tiunov Alexander E. Ulanov A. I. Lvovsky	2
+	On the computational complexity of Ising spin glass models	1982	Francisco Barahona	2
+ PDF Chat	Optimization by quantum annealing: Lessons from hard satisfiability problems	2005	Demian Battaglia Giuseppe E. Santoro Erio Tosatti	2
+ PDF Chat	Destabilization of Local Minima in Analog Spin Systems by Correction of Amplitude Heterogeneity	2019	Timothée Leleu Y. Yamamoto Peter L. McMahon Kazuyuki Aihara	2
+ PDF Chat	Rotation-invariant convolutional neural networks for galaxy morphology prediction	2015	Sander Dieleman Kyle Willett Joni Dambre	2
+ PDF Chat	A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem	2001	Edward Farhi Jeffrey Goldstone Sam Gutmann Joshua M. Lapan A. P. Lundgren Daniel Preda	2
+	Crystal Statistics. I. A Two-Dimensional Model with an Order-Disorder Transition	1944	Lars Onsager	2
+ PDF Chat	Theory of Quantum Annealing of an Ising Spin Glass	2002	Giuseppe E. Santoro Roman Martoňák Erio Tosatti Roberto Car	2
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	2
+ PDF Chat	Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning	2012	Matthias Rupp Alexandre Tkatchenko Klaus‐Robert Müller O. Anatole von Lilienfeld	2
+ PDF Chat	Discovering phase transitions with unsupervised learning	2016	Lei Wang	2
+ PDF Chat	Efficient Quantum and Simulated Annealing of Potts Models Using a Half-hot Constraint	2020	Shuntaro Okada Masayuki Ohzeki Kazuyuki Tanaka	2
+ PDF Chat	Experimental demonstration of a robust and scalable flux qubit	2010	R. Harris Jonas Johansson A. J. Berkley Mark W. Johnson T. Lanting Siyuan Han P. Bunyk E. Ladizinsky T. Oh I. Perminov	2
+ PDF Chat	Architectural Considerations in the Design of a Superconducting Quantum Annealing Processor	2014	P. Bunyk Emile Hoskinson Mark W. Johnson E. Tolkacheva Fabio Altomare A. J. Berkley R. Harris Jeremy Hilton T. Lanting Anthony Przybysz	2
+ PDF Chat	Evidence for quantum annealing with more than one hundred qubits	2014	Sergio Boixo Troels F. Rønnow Sergei V. Isakov Zhihui Wang D. Wecker Daniel A. Lidar John M. Martinis Matthias Troyer	2
+ PDF Chat	Experimental investigation of an eight-qubit unit cell in a superconducting optimization processor	2010	R. Harris Mark W. Johnson T. Lanting A. J. Berkley Jonas Johansson P. Bunyk E. Tolkacheva E. Ladizinsky N. Ladizinsky T. Oh	2
+ PDF Chat	Deep neural networks for direct, featureless learning through observation: The case of two-dimensional spin models	2018	Kyle Mills Isaac Tamblyn	2
+ PDF Chat	Quantum annealing in the transverse Ising model	1998	Tadashi Kadowaki Hidetoshi Nishimori	2
+	Monte Carlo sampling methods using Markov chains and their applications	1970	W. Keith Hastings	2
+ PDF Chat	Entropy Production along a Stochastic Trajectory and an Integral Fluctuation Theorem	2005	Udo Seifert	1
+	Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach	2015	Raghunathan Ramakrishnan Pavlo O. Dral Matthias Rupp O. Anatole von Lilienfeld	1
+ PDF Chat	Topological Entanglement Entropy	2006	Alexei Kitaev John Preskill	1
+ PDF Chat	Biochemical Machines for the Interconversion of Mutual Information and Work	2017	Thomas McGrath Nick S. Jones Pieter Rein ten Wolde Thomas E. Ouldridge	1
+ PDF Chat	A convolutional neural network neutrino event classifier	2016	A. Aurisano A. Radovic D. Rocco A. Himmel M. D. Messier E. Niner G. Pawloski F. Psihas A. Sousa P. Vahle	1
+ PDF Chat	Comparing molecules and solids across structural and alchemical space	2016	Sandip De Albert P. Bartók Gábor Cśanyi Michele Ceriotti	1
+ PDF Chat	First-order dynamical phase transition in models of glasses: an approach based on ensembles of histories	2009	Juan P. Garrahan Robert L. Jack Vivien Lecomte Estelle Pitard Kristina van Duijvendijk Frédéric van Wijland	1
+ PDF Chat	Ultracold atomic gases in optical lattices: mimicking condensed matter physics and beyond	2007	Maciej Lewenstein Anna Sanpera V. Ahufinger Bogdan Damski Aditi Sen Ujjwal Sen	1
+ PDF Chat	Machine Learning Energies of 2 Million Elpasolite<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mi>A</mml:mi><mml:mi>B</mml:mi><mml:msub><mml:mrow><mml:mi>C</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub><mml:msub><mml:mrow><mml:mi>D</mml:mi></mml:mrow><mml:mrow><mml:mn>6</mml:mn></mml:mrow></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math>Crystals	2016	Felix A. Faber Alexander Lindmaa O. Anatole von Lilienfeld Rickard Armiento	1
+ PDF Chat	Molecular graph convolutions: moving beyond fingerprints	2016	Steven Kearnes Kevin McCloskey Marc Berndl Vijay S. Pande Patrick Riley	1