The University of British Columbia

∙ Vancouver , Canada ∙ 0 followers

25306 The University of British Columbia is a public research university with campuses in Vancouver and Kelowna, British Columbia.

Featured Researchers

Hao Chen
141 publications
Yu Wang
129 publications
Nando de Freitas
72 publications
Frank Hutter
70 publications
Frank Wood
63 publications
Arnaud Doucet
56 publications
Leonid Sigal
52 publications
Mark Schmidt
44 publications
Chen Feng
40 publications
Ziyu Wang
38 publications
Aleksandr Y. Aravkin
38 publications

AttentionRNN: A Structured Spatial Attention Mechanism

Visual attention mechanisms have proven to be integrally important const...
05/22/2019 ∙ by Siddhesh Khandelwal, et al. ∙ 31 ∙ share

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AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks

Recurrent neural networks have gained widespread use in modeling sequent...
02/26/2019 ∙ by Bo Chang, et al. ∙ 24 ∙ share

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A Preliminary Study of Disentanglement With Insights on the Inadequacy of Metrics

Disentangled encoding is an important step towards a better representati...
11/26/2019 ∙ by Amir H. Abdi, et al. ∙ 15 ∙ share

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Building Ethics into Artificial Intelligence

As artificial intelligence (AI) systems become increasingly ubiquitous, ...
12/07/2018 ∙ by Han Yu, et al. ∙ 14 ∙ share

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Imitation Learning of Factored Multi-agent Reactive Models

We apply recent advances in deep generative modeling to the task of imit...
03/12/2019 ∙ by Michael Teng, et al. ∙ 11 ∙ share

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The role of surrogate models in the development of digital twins of dynamic systems

Digital twin technology has significant promise, relevance and potential...
01/25/2020 ∙ by Souvik Chakraborty, et al. ∙ 11 ∙ share

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Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates

Recent works have shown that stochastic gradient descent (SGD) achieves ...
05/24/2019 ∙ by Sharan Vaswani, et al. ∙ 10 ∙ share

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Neural Sequential Phrase Grounding (SeqGROUND)

We propose an end-to-end approach for phrase grounding in images. Unlike...
03/18/2019 ∙ by Pelin Dogan, et al. ∙ 8 ∙ share

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Valid Causal Inference with (Some) Invalid Instruments

Instrumental variable methods provide a powerful approach to estimating ...
06/19/2020 ∙ by Jason Hartford, et al. ∙ 8 ∙ share

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Smarter Parking: Using AI to Identify Parking Inefficiencies in Vancouver

On-street parking is convenient, but has many disadvantages: on-street s...
03/21/2020 ∙ by Devon Graham, et al. ∙ 7 ∙ share

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Distilling and Transferring Knowledge via cGAN-generated Samples for Image Classification and Regression

Knowledge distillation (KD) has been actively studied for image classifi...
04/07/2021 ∙ by Xin Ding, et al. ∙ 7 ∙ share

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Learning Sports Camera Selection from Internet Videos

This work addresses camera selection, the task of predicting which camer...
09/08/2018 ∙ by Jianhui Chen, et al. ∙ 6 ∙ share

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Instance-level Facial Attributes Transfer with Geometry-Aware Flow

We address the problem of instance-level facial attribute transfer witho...
11/30/2018 ∙ by Weidong Yin, et al. ∙ 6 ∙ share

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CHAIN: Concept-harmonized Hierarchical Inference Interpretation of Deep Convolutional Neural Networks

With the great success of networks, it witnesses the increasing demand f...
02/05/2020 ∙ by Dan Wang, et al. ∙ 6 ∙ share

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Coping With Simulators That Don't Always Return

Deterministic models are approximations of reality that are easy to inte...
03/28/2020 ∙ by Andrew Warrington, et al. ∙ 6 ∙ share

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Learning Joint Articulatory-Acoustic Representations with Normalizing Flows

The articulatory geometric configurations of the vocal tract and the aco...
05/16/2020 ∙ by Pramit Saha, et al. ∙ 6 ∙ share

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PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers

Local processing is an essential feature of CNNs and other neural networ...
11/27/2020 ∙ by Frank Yu, et al. ∙ 6 ∙ share

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Efficient Deep Gaussian Process Models for Variable-Sized Input

Deep Gaussian processes (DGP) have appealing Bayesian properties, can ha...
05/16/2019 ∙ by Issam H. Laradji, et al. ∙ 5 ∙ share

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Joint User Pairing and Association for Multicell NOMA: A Pointer Network-based Approach

In this paper, we investigate the joint user pairing and association pro...
04/15/2020 ∙ by Manyou Ma, et al. ∙ 5 ∙ share

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Ultra2Speech – A Deep Learning Framework for Formant Frequency Estimation and Tracking from Ultrasound Tongue Images

Thousands of individuals need surgical removal of their larynx due to cr...
06/29/2020 ∙ by Pramit Saha, et al. ∙ 5 ∙ share

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Hierarchical Marketing Mix Models with Sign Constraints

Marketing mix models (MMMs) are statistical models for measuring the eff...
08/28/2020 ∙ by Hao Chen, et al. ∙ 5 ∙ share

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Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model

We present a novel framework that enables efficient probabilistic infere...
07/20/2018 ∙ by Atilim Gunes Baydin, et al. ∙ 4 ∙ share

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Does Your Model Know the Digit 6 Is Not a Cat? A Less Biased Evaluation of "Outlier" Detectors

In the real world, a learning system could receive an input that looks n...
09/13/2018 ∙ by Alireza Shafaei, et al. ∙ 4 ∙ share

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LayoutVAE: Stochastic Scene Layout Generation from a Label Set

Recently there is an increasing interest in scene generation within the ...
07/24/2019 ∙ by Akash Abdu Jyothi, et al. ∙ 3 ∙ share

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Inference Trees: Adaptive Inference with Exploration

We introduce inference trees (ITs), a new class of inference methods tha...
06/25/2018 ∙ by Tom Rainforth, et al. ∙ 2 ∙ share

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Where are the Blobs: Counting by Localization with Point Supervision

Object counting is an important task in computer vision due to its growi...
07/25/2018 ∙ by Issam H. Laradji, et al. ∙ 2 ∙ share

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An Introduction to Probabilistic Programming

This document is designed to be a first-year graduate-level introduction...
09/27/2018 ∙ by Jan-Willem van de Meent, et al. ∙ 2 ∙ share

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Instance Segmentation with Point Supervision

Instance segmentation methods often require costly per-pixel labels. We ...
06/14/2019 ∙ by Issam H. Laradji, et al. ∙ 2 ∙ share

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Assisting the Adversary to Improve GAN Training

We propose a method for improved training of generative adversarial netw...
10/03/2020 ∙ by Andreas Munk, et al. ∙ 2 ∙ share

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M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning

Unsupervised domain adaptation techniques have been successful for a wid...
07/06/2018 ∙ by Issam Laradji, et al. ∙ 1 ∙ share

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Predicting Confusion from Eye-Tracking Data with Recurrent Neural Networks

Encouraged by the success of deep learning in a variety of domains, we i...
06/19/2019 ∙ by Shane D. Sims, et al. ∙ 1 ∙ share

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Improved Few-Shot Visual Classification

Few-shot learning is a fundamental task in computer vision that carries ...
12/07/2019 ∙ by Peyman Bateni, et al. ∙ 1 ∙ share

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Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval

This paper develops a model that addresses sentence embedding, a hot top...
02/24/2015 ∙ by Hamid Palangi, et al. ∙ 0 ∙ share

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On Integrating Information Visualization Techniques into Data Mining: A Review

The exploding growth of digital data in the information era and its imme...
03/01/2015 ∙ by Keqian Li, et al. ∙ 0 ∙ share

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Multi-Channel CNN-based Object Detection for Enhanced Situation Awareness

Object Detection is critical for automatic military operations. However,...
11/30/2017 ∙ by Shuo Liu, et al. ∙ 0 ∙ share

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Exploiting temporal information for 3D pose estimation

In this work, we address the problem of 3D human pose estimation from a ...
11/23/2017 ∙ by Mir Rayat Imtiaz Hossain, et al. ∙ 0 ∙ share

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Recent Advances in Zero-shot Recognition

With the recent renaissance of deep convolution neural networks, encoura...
10/13/2017 ∙ by Yanwei Fu, et al. ∙ 0 ∙ share

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Learning across scales - A multiscale method for Convolution Neural Networks

In this work we establish the relation between optimal control and train...
03/06/2017 ∙ by Eldad Haber, et al. ∙ 0 ∙ share

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Backtracking Regression Forests for Accurate Camera Relocalization

Camera relocalization plays a vital role in many robotics and computer v...
10/22/2017 ∙ by Lili Meng, et al. ∙ 0 ∙ share

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Generalized Haar Filter based Deep Networks for Real-Time Object Detection in Traffic Scene

Vision-based object detection is one of the fundamental functions in num...
10/30/2016 ∙ by Keyu Lu, et al. ∙ 0 ∙ share

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Domain Recursion for Lifted Inference with Existential Quantifiers

In recent work, we proved that the domain recursion inference rule makes...
07/24/2017 ∙ by Seyed Mehran Kazemi, et al. ∙ 0 ∙ share

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Hot-Rodding the Browser Engine: Automatic Configuration of JavaScript Compilers

Modern software systems in many application areas offer to the user a mu...
07/11/2017 ∙ by Chris Fawcett, et al. ∙ 0 ∙ share

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Reversible Architectures for Arbitrarily Deep Residual Neural Networks

Recently, deep residual networks have been successfully applied in many ...
09/12/2017 ∙ by Bo Chang, et al. ∙ 0 ∙ share

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Deep Optimization for Spectrum Repacking

Over 13 months in 2016-17 the FCC conducted an "incentive auction" to re...
06/11/2017 ∙ by Neil Newman, et al. ∙ 0 ∙ share

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Reduced-Precision Strategies for Bounded Memory in Deep Neural Nets

This work investigates how using reduced precision data in Convolutional...
11/17/2015 ∙ by Patrick Judd, et al. ∙ 0 ∙ share

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Ensembles of Models and Metrics for Robust Ranking of Homologous Proteins

An ensemble of models (EM), where each model is constructed on a diverse...
06/21/2017 ∙ by Jabed H Tomal, et al. ∙ 0 ∙ share

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New Liftable Classes for First-Order Probabilistic Inference

Statistical relational models provide compact encodings of probabilistic...
10/26/2016 ∙ by Seyed Mehran Kazemi, et al. ∙ 0 ∙ share

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A Learning Algorithm for Relational Logistic Regression: Preliminary Results

Relational logistic regression (RLR) is a representation of conditional ...
06/28/2016 ∙ by Bahare Fatemi, et al. ∙ 0 ∙ share

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Why is Compiling Lifted Inference into a Low-Level Language so Effective?

First-order knowledge compilation techniques have proven efficient for l...
06/14/2016 ∙ by Seyed Mehran Kazemi, et al. ∙ 0 ∙ share

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Weakly-Supervised Spatial Context Networks

We explore the power of spatial context as a self-supervisory signal for...
04/10/2017 ∙ by Zuxuan Wu, et al. ∙ 0 ∙ share

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