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.

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

read it
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

read it
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

read it
Building Ethics into Artificial Intelligence

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
Generalizing Prototype Theory: A Formal Quantum Framework

Theories of natural language and concepts have been unable to model the ...
01/25/2016 ∙ by Diederik Aerts, et al. ∙ 0 ∙ share

read it
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition

In 1963, Polyak proposed a simple condition that is sufficient to show a...
08/16/2016 ∙ by Hamed Karimi, et al. ∙ 0 ∙ share

read it

The University of British Columbia

Featured Researchers