NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (71)

cs.DS2013

Partition-Merge: Distributed Inference and Modularity Optimization

Vincent Blondel, Kyomin Jung, Pushmeet Kohli +1

cs.CV2015

Deep Convolutional Inverse Graphics Network

Tejas D. Kulkarni, Will Whitney, Pushmeet Kohli +1

cs.AI2019

Value Propagation Networks

Nantas Nardelli, Gabriel Synnaeve, Zeming Lin +3

cs.CV2017

Memory-augmented Attention Modelling for Videos

Rasool Fakoor, Abdel-rahman Mohamed, Margaret Mitchell +2

stat.ML2018

Batched High-dimensional Bayesian Optimization via Structural Kernel Learning

Zi Wang, Chengtao Li, Stefanie Jegelka +1

cs.AI2017

Deep API Programmer: Learning to Program with APIs

Surya Bhupatiraju, Rishabh Singh, Abdel-rahman Mohamed +1

cs.CV2016

Efficient Continuous Relaxations for Dense CRF

Alban Desmaison, Rudy Bunel, Pushmeet Kohli +2

cs.CV2013

Efficient Energy Minimization for Enforcing Statistics

Yongsub Lim, Kyomin Jung, Pushmeet Kohli

cs.LG2018

Training verified learners with learned verifiers

Krishnamurthy Dvijotham, Sven Gowal, Robert Stanforth +4

cs.CV2014

Inverse Graphics with Probabilistic CAD Models

Tejas D. Kulkarni, Vikash K. Mansinghka, Pushmeet Kohli +1

cs.AI2016

Neuro-Symbolic Program Synthesis

Emilio Parisotto, Abdel-rahman Mohamed, Rishabh Singh +3

cs.LG2016

TerpreT: A Probabilistic Programming Language for Program Induction

Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh +4

cs.CV2018

Efficient Relaxations for Dense CRFs with Sparse Higher Order Potentials

Thomas Joy, Alban Desmaison, Thalaiyasingam Ajanthan +5

cs.CV2014

Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions

Roman Shapovalov, Dmitry Vetrov, Anton Osokin +1

cs.LG2015

Efficient non-greedy optimization of decision trees

Mohammad Norouzi, Maxwell D. Collins, Matthew Johnson +2

cs.LG2015

CO2 Forest: Improved Random Forest by Continuous Optimization of Oblique Splits

Mohammad Norouzi, Maxwell D. Collins, David J. Fleet +1

cs.LG2016

Batched Gaussian Process Bandit Optimization via Determinantal Point Processes

Tarun Kathuria, Amit Deshpande, Pushmeet Kohli

cs.LG2013

Multi-dimensional Parametric Mincuts for Constrained MAP Inference

Yongsub Lim, Kyomin Jung, Pushmeet Kohli

cs.LG2019

Programmatically Interpretable Reinforcement Learning

Abhinav Verma, Vijayaraghavan Murali, Rishabh Singh +2

cs.LG2019

Analysing Mathematical Reasoning Abilities of Neural Models

David Saxton, Edward Grefenstette, Felix Hill +1

cs.CL2016

A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories

Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He +5

cs.AI2018

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning

Jakob Foerster, Nantas Nardelli, Gregory Farquhar +4

cs.LG2018

A Dual Approach to Scalable Verification of Deep Networks

Krishnamurthy, Dvijotham, Robert Stanforth +3

cs.CL2016

Visual Storytelling

Ting-Hao, Huang, Francis Ferraro +13

cs.CV2019

The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

Jiayuan Mao, Chuang Gan, Pushmeet Kohli +2

cs.LG2019

Structured agents for physical construction

Victor Bapst, Alvaro Sanchez-Gonzalez, Carl Doersch +4

cs.AI2017

Neural Program Meta-Induction

Jacob Devlin, Rudy Bunel, Rishabh Singh +2

cs.LG2018

Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis

Rudy Bunel, Matthew Hausknecht, Jacob Devlin +2

cs.CV2015

Consensus Message Passing for Layered Graphical Models

Varun Jampani, S. M. Ali Eslami, Daniel Tarlow +2

stat.ML2018

Batched Large-scale Bayesian Optimization in High-dimensional Spaces

Zi Wang, Clement Gehring, Pushmeet Kohli +1

cs.LG2016

Learning to superoptimize programs - Workshop Version

Rudy Bunel, Alban Desmaison, M. Pawan Kumar +2

cs.LG2016

Summary - TerpreT: A Probabilistic Programming Language for Program Induction

Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh +4

stat.ML2016

Inducing Interpretable Representations with Variational Autoencoders

N. Siddharth, Brooks Paige, Alban Desmaison +5

stat.ML2019

Degenerate Feedback Loops in Recommender Systems

Ray Jiang, Silvia Chiappa, Tor Lattimore +2

cs.AI2017

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning

Junhyuk Oh, Satinder Singh, Honglak Lee +1

cs.AI2015

Information Gathering in Networks via Active Exploration

Adish Singla, Eric Horvitz, Pushmeet Kohli +2

cs.CV2014

Memory Bounded Deep Convolutional Networks

Maxwell D. Collins, Pushmeet Kohli

cs.LG2017

Learning Continuous Semantic Representations of Symbolic Expressions

Miltiadis Allamanis, Pankajan Chanthirasegaran, Pushmeet Kohli +1

cs.AI2017

Semantic Code Repair using Neuro-Symbolic Transformation Networks

Jacob Devlin, Jonathan Uesato, Rishabh Singh +1

cs.CV2016

Learning to Navigate the Energy Landscape

Julien Valentin, Angela Dai, Matthias Nießner +4

cs.CV2011

Curvature Prior for MRF-based Segmentation and Shape Inpainting

Alexander Shekhovtsov, Pushmeet Kohli, Carsten Rother

cs.LG2018

Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures

Jonathan Uesato, Ananya Kumar, Csaba Szepesvari +7

cs.CV2017

DeepContext: Context-Encoding Neural Pathways for 3D Holistic Scene Understanding

Yinda Zhang, Mingru Bai, Pushmeet Kohli +2

cs.LG2019

Graph Matching Networks for Learning the Similarity of Graph Structured Objects

Yujia Li, Chenjie Gu, Thomas Dullien +2

cs.LG2019

Verification of Non-Linear Specifications for Neural Networks

Chongli Qin, Krishnamurthy, Dvijotham +7

cs.LG2018

Relational inductive biases, deep learning, and graph networks

Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst +24

cs.CV2016

Deep disentangled representations for volumetric reconstruction

Edward Grant, Pushmeet Kohli, Marcel van Gerven

cs.NE2018

Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles

Edward Grefenstette, Robert Stanforth, Brendan O'Donoghue +3

stat.ML2017

Learning Disentangled Representations with Semi-Supervised Deep Generative Models

N. Siddharth, Brooks Paige, Jan-Willem van de Meent +5

cs.CV2016

PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions

Michael Figurnov, Aijan Ibraimova, Dmitry Vetrov +1

cs.NE2018

Can Neural Networks Understand Logical Entailment?

Richard Evans, David Saxton, David Amos +2

stat.ML2009

Learning an Interactive Segmentation System

Hannes Nickisch, Pushmeet Kohli, Carsten Rother

cs.AI2012

Exact and Approximate Inference in Associative Hierarchical Networks using Graph Cuts

Chris Russell, L'ubor Ladicky, Pushmeet Kohli +1

cs.CV2016

Deep Multi-Modal Image Correspondence Learning

Chen Liu, Jiajun Wu, Pushmeet Kohli +1

stat.ML2019

Meta-Learning surrogate models for sequential decision making

Alexandre Galashov, Jonathan Schwarz, Hyunjik Kim +5

cs.AI2019

Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding

Kexin Yi, Jiajun Wu, Chuang Gan +3

cs.LG2018

Verification of deep probabilistic models

Krishnamurthy Dvijotham, Marta Garnelo, Alhussein Fawzi +1

cs.LG2018

Adversarial Risk and the Dangers of Evaluating Against Weak Attacks

Jonathan Uesato, Brendan O'Donoghue, Aaron van den Oord +1

cs.AI2018

A Unified View of Piecewise Linear Neural Network Verification

Rudy Bunel, Ilker Turkaslan, Philip H. S. Torr +2

cs.AI2016

Adaptive Neural Compilation

Rudy Bunel, Alban Desmaison, Pushmeet Kohli +2

cs.LG2017

Learning to superoptimize programs

Rudy Bunel, Alban Desmaison, M. Pawan Kumar +2

cs.LG2018

Scaling shared model governance via model splitting

Miljan Martic, Jan Leike, Andrew Trask +3

cs.CV2016

Multi-way Particle Swarm Fusion

Chen Liu, Hang Yan, Pushmeet Kohli +1

cs.AI2016

Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems

Matteo Venanzi, John Guiver, Pushmeet Kohli +1

cs.CV2013

A two-layer Conditional Random Field for the classification of partially occluded objects

Sergey Kosov, Pushmeet Kohli, Franz Rottensteiner +1

cs.GT2013

Optimal Coalition Structures in Cooperative Graph Games

Yoram Bachrach, Pushmeet Kohli, Vladimir Kolmogorov +1

cs.CV2019

A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities

Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein +5

stat.ML2019

CompILE: Compositional Imitation Learning and Execution

Thomas Kipf, Yujia Li, Hanjun Dai +5

cs.LG2019

Knowing When to Stop: Evaluation and Verification of Conformity to Output-size Specifications

Chenglong Wang, Rudy Bunel, Krishnamurthy Dvijotham +3

cs.HC2015

Learning to Hire Teams

Adish Singla, Eric Horvitz, Pushmeet Kohli +1

cs.AI2017

RobustFill: Neural Program Learning under Noisy I/O

Jacob Devlin, Jonathan Uesato, Surya Bhupatiraju +3