Search Results

Qiskit Pulse: Programming Quantum Computers Through the Cloud with Pulses

2 code implementations14 Apr 2020

To demonstrate the capabilities of Qiskit Pulse, we calibrate both un-echoed and echoed variants of the cross-resonance entangling gate with a pair of qubits on an IBM Quantum system accessible through the cloud.

Quantum Physics

SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusion

2 code implementations18 Jun 2019

The availability of curated large-scale training data is a crucial factor for the development of well-generalizing deep learning methods for the extraction of geoinformation from multi-sensor remote sensing imagery.

Cloud Computing Scene Classification +1

PennyLane: Automatic differentiation of hybrid quantum-classical computations

26 code implementations12 Nov 2018

PennyLane's core feature is the ability to compute gradients of variational quantum circuits in a way that is compatible with classical techniques such as backpropagation.

BIG-bench Machine Learning Quantum Machine Learning

GSPMD: General and Scalable Parallelization for ML Computation Graphs

1 code implementation10 May 2021

We present GSPMD, an automatic, compiler-based parallelization system for common machine learning computations.

Playing the Game of 2048

Couler: Unified Machine Learning Workflow Optimization in Cloud

1 code implementation12 Mar 2024

This variety poses a challenge for end-users in terms of mastering different engine APIs.

Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection

4 code implementations18 Sep 2019

In this paper, we enable the simultaneous use of non-minimal solvers and robust estimation by providing a general-purpose approach for robust global estimation, which can be applied to any problem where a non-minimal solver is available for the outlier-free case.

Pose Estimation

Flower: A Friendly Federated Learning Research Framework

1 code implementation28 Jul 2020

Federated Learning (FL) has emerged as a promising technique for edge devices to collaboratively learn a shared prediction model, while keeping their training data on the device, thereby decoupling the ability to do machine learning from the need to store the data in the cloud.

Federated Learning

Learning to Segment 3D Point Clouds in 2D Image Space

1 code implementation CVPR 2020

In contrast to the literature where local patterns in 3D point clouds are captured by customized convolutional operators, in this paper we study the problem of how to effectively and efficiently project such point clouds into a 2D image space so that traditional 2D convolutional neural networks (CNNs) such as U-Net can be applied for segmentation.

3D Part Segmentation graph construction +1

Private delegated computations using strong isolation

1 code implementation6 May 2022

Sensitive computations are now routinely delegated to third-parties.

Cryptography and Security Operating Systems Programming Languages