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Greatest papers with code

Relocalization, Global Optimization and Map Merging for Monocular Visual-Inertial SLAM

5 Mar 2018HKUST-Aerial-Robotics/VINS-Mono

In this paper, we propose a monocular visual-inertial SLAM system, which can relocalize camera and get the absolute pose in a previous-built map.

GLOBAL OPTIMIZATION POSE ESTIMATION

BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization

NeurIPS 2020 pytorch/botorch

Bayesian optimization provides sample-efficient global optimization for a broad range of applications, including automatic machine learning, engineering, physics, and experimental design.

BAYESIAN OPTIMISATION GLOBAL OPTIMIZATION

Bayesian Optimization with Unknown Constraints

22 Mar 2014HIPS/Spearmint

Recent work on Bayesian optimization has shown its effectiveness in global optimization of difficult black-box objective functions.

GLOBAL OPTIMIZATION

Input Warping for Bayesian Optimization of Non-stationary Functions

5 Feb 2014HIPS/Spearmint

Bayesian optimization has proven to be a highly effective methodology for the global optimization of unknown, expensive and multimodal functions.

GAUSSIAN PROCESSES GLOBAL OPTIMIZATION

A Modular Task-oriented Dialogue System Using a Neural Mixture-of-Experts

10 Jul 2019budzianowski/multiwoz

We propose a neural Modular Task-oriented Dialogue System(MTDS) framework, in which a few expert bots are combined to generate the response for a given dialogue context.

GLOBAL OPTIMIZATION TASK-ORIENTED DIALOGUE SYSTEMS

Slot-Gated Modeling for Joint Slot Filling and Intent Prediction

NAACL 2018 MiuLab/SlotGated-SLU

Attention-based recurrent neural network models for joint intent detection and slot filling have achieved the state-of-the-art performance, while they have independent attention weights.

GLOBAL OPTIMIZATION INTENT DETECTION SLOT FILLING SPOKEN DIALOGUE SYSTEMS SPOKEN LANGUAGE UNDERSTANDING

Bayesian Optimization with Gradients

NeurIPS 2017 wujian16/Cornell-MOE

Bayesian optimization has been successful at global optimization of expensive-to-evaluate multimodal objective functions.

GLOBAL OPTIMIZATION

pySOT and POAP: An event-driven asynchronous framework for surrogate optimization

30 Jul 2019dme65/pySOT

This paper describes Plumbing for Optimization with Asynchronous Parallelism (POAP) and the Python Surrogate Optimization Toolbox (pySOT).

GLOBAL OPTIMIZATION

On the implementation of a global optimization method for mixed-variable problems

4 Sep 2020coin-or/rbfopt

We describe the optimization algorithm implemented in the open-source derivative-free solver RBFOpt.

GLOBAL OPTIMIZATION

Understanding the wiring evolution in differentiable neural architecture search

2 Sep 2020SNAS-Series/SNAS-Series

To this end, we pose questions that future differentiable methods for neural wiring discovery need to confront, hoping to evoke a discussion and rethinking on how much bias has been enforced implicitly in existing NAS methods.

GLOBAL OPTIMIZATION NEURAL ARCHITECTURE SEARCH