Home      Discussions      About
Join us
Ask Question
Latest Conferences Trending
ICLR
NIPS
ICML
CVPR
ICCV
ECCV
ICRA
MICCAI
IROS
IJRR
RLDM
ICLR 2019
Jan 29, 2016
From NIPS
Machine Learning
Computer Vision
Neurons and Cognition

Mapping Tractography Across Subjects

Diffusion magnetic resonance imaging (dMRI) and tractography provide means to study the anatomical structures within the white matter of the brain....
Mar 08, 2016
From ICLR
Computer Vision

A New Method to Visualize Deep Neural Networks

We present a method for visualising the response of a deep neural network to a specific input. For image data for instance our method will highligh...
Mar 02, 2018
By sachinr
From ICLR
Machine Learning
Computer Vision

Meta-Learning for Semi-Supervised Few-Shot Classification

In few-shot classification, we are interested in learning algorithms that train a classifier from only a handful of labeled examples. Recent progre...
Sep 26, 2016
By pfmark
From ICRA
Robotics

From Perception to Decision: A Data-driven Approach to End-to-end M...

Learning from demonstration for motion planning is an ongoing research topic. In this paper we present a model that is able to learn the complex ma...
Sep 07, 2017
From ICML
Cryptography and Security
Machine Learning

RNN-based Early Cyber-Attack Detection for the Tennessee Eastman Pr...

An RNN-based forecasting approach is used to early detect anomalies in industrial multivariate time series data from a simulated Tennessee Eastman ...
Oct 16, 2017
From ICRA
Computer Vision
Robotics

What is (missing or wrong) in the scene? A Hybrid Deep Boltzmann Ma...

Scene models allow robots to reason about what is in the scene, what else should be in it, and what should not be in it. In this paper, we propose ...
May 21, 2016
From ICML
Neural and Evolutionary Computation
Artificial Intelligence
Machine Learning

Programming with a Differentiable Forth Interpreter

Given that in practice training data is scarce for all but a small set of problems, a core question is how to incorporate prior knowledge into a mo...
Mar 26, 2018
By hui
From CVPR
Computer Vision

Fast and Accurate Single Image Super-Resolution via Information D...

Recently, deep convolutional neural networks (CNNs) have been demonstrated remarkable progress on single image super-resolution. However, as the de...
Feb 28, 2017
By mstaib
From ICML
Machine Learning
Artificial Intelligence
Data Structures and Algorithms
Social and Information Networks
Optimization and Control

Robust Budget Allocation via Continuous Submodular Functions

The optimal allocation of resources for maximizing influence, spread of information or coverage, has gained attention in the past years, in particu...
Sep 14, 2017
From IROS
Robotics
Computer Vision
Machine Learning

From Plants to Landmarks: Time-invariant Plant Localization that us...

Agricultural robots are expected to increase yields in a sustainable way and automate precision tasks, such as weeding and plant monitoring. At the...
Oct 01, 2018
From ICLR 2019
Machine Learning

Set Transformer

Many machine learning tasks such as multiple instance learning, 3D shape recognition and few-shot image classification are defined on sets of insta...
Mar 22, 2017
From CVPR
Computer Vision

Video Frame Interpolation via Adaptive Convolution

Video frame interpolation typically involves two steps: motion estimation and pixel synthesis. Such a two-step approach heavily depends on the qual...
Dec 07, 2017
By jlu23
From CVPR
Computer Vision
Artificial Intelligence
Graphics
Machine Learning

Adversarial Examples that Fool Detectors

An adversarial example is an example that has been adjusted to produce a wrong label when presented to a system at test time. To date, adversarial ...
Feb 21, 2017
From CVPR
Computer Vision

Object Detection in Videos with Tubelet Proposal Networks

Object detection in videos has drawn increasing attention recently with the introduction of the large-scale ImageNet VID dataset. Different from ob...
Aug 13, 2014
From ICML
Machine Learning

Fastfood: Approximate Kernel Expansions in Loglinear Time

Despite their successes, what makes kernel methods difficult to use in many large scale problems is the fact that storing and computing the decisio...
Oct 17, 2018
By ywang
From ICLR 2019
Artificial Intelligence
Machine Learning

On Evaluating Embedding Models for Knowledge Base Completion

Knowledge bases contribute to many artificial intelligence tasks, yet they are often incomplete. To add missing facts to a given knowledge base, va...
Jun 01, 2017
By nsid
From NIPS
Machine Learning
Artificial Intelligence

Learning Disentangled Representations with Semi-Supervised Deep G...

Variational autoencoders (VAEs) learn representations of data by jointly training a probabilistic encoder and decoder network. Typically these mode...
Jul 27, 2016
From ECCV
Computer Vision

A Continuous Optimization Approach for Efficient and Accurate Scene...

We propose a continuous optimization method for solving dense 3D scene flow problems from stereo imagery. As in recent work, we represent the dynam...
Feb 26, 2018
From CVPR
Computer Vision

2D/3D Pose Estimation and Action Recognition using Multitask Deep ...

Action recognition and human pose estimation are closely related but both problems are generally handled as distinct tasks in the literature. In th...
Oct 12, 2016
From NIPS
Machine Learning
Discrete Mathematics
Logic in Computer Science
Combinatorics

On statistical learning via the lens of compression

This work continues the study of the relationship between sample compression schemes and statistical learning, which has been mostly investigated w...
There aren't more projects

Every arXiv paper needs to be discussed

Request Comment

or Invite via email
You are asking your first question!
How to quickly get a good answer:
  • Keep your question short and to the point
  • Check for grammar or spelling errors.
  • Phrase it like a question
Test
Test description