This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.

Overview

This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.

This replication package contains the following parts:

  • experiment results/ contains the experimental results for the six open source models
  • implementation/ contains the code for training the six open source models
  • record-and-replay/ contains the binary format of the record-and-replay tool
  • Time.xlsx contains the table for the time overhead comparison

To use the record-and-replay tool, in Linux, point the absolute location to LD_PRELOAD and start the training process as usual. Check the system log: cat /var/log/syslog


For the semi-formal interview:

We worked closely with ~20 practitioners, who are either senior software developers or ML scientists with Ph.D. degrees. Their tasks are to prototype DL models and/or productionalize DL models. We have conducted two separate interviews with them and each round lasted for about 2 hours. During the interview, we presented our survey on the state-of-the-art techniques towards reproducibility and gathered their feedback (reported in Section 2.3).

Code related to the manuscript "Averting A Crisis In Simulation-Based Inference"

Abstract We present extensive empirical evidence showing that current Bayesian simulation-based inference algorithms are inadequate for the falsificat

Montefiore Artificial Intelligence Research 3 Nov 14, 2022
FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack

FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack Case study of the FCA. The code can be find in FCA. Cas

IDRL 21 Dec 15, 2022
This repository contains code to train and render Mixture of Volumetric Primitives (MVP) models

Mixture of Volumetric Primitives -- Training and Evaluation This repository contains code to train and render Mixture of Volumetric Primitives (MVP) m

Meta Research 125 Dec 29, 2022
Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking

Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking We revisit and address issues with Oxford 5k and Paris 6k image retrieval benchm

Filip Radenovic 188 Dec 17, 2022
Implementation of " SESS: Self-Ensembling Semi-Supervised 3D Object Detection" (CVPR2020 Oral)

SESS: Self-Ensembling Semi-Supervised 3D Object Detection Created by Na Zhao from National University of Singapore Introduction This repository contai

125 Dec 23, 2022
High performance Cross-platform Inference-engine, you could run Anakin on x86-cpu,arm, nv-gpu, amd-gpu,bitmain and cambricon devices.

Anakin2.0 Welcome to the Anakin GitHub. Anakin is a cross-platform, high-performance inference engine, which is originally developed by Baidu engineer

514 Dec 28, 2022
Efficient 3D Backbone Network for Temporal Modeling

VoV3D is an efficient and effective 3D backbone network for temporal modeling implemented on top of PySlowFast. Diverse Temporal Aggregation and

102 Dec 06, 2022
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

880 Jan 07, 2023
Code for the Interspeech 2021 paper "AST: Audio Spectrogram Transformer".

AST: Audio Spectrogram Transformer Introduction Citing Getting Started ESC-50 Recipe Speechcommands Recipe AudioSet Recipe Pretrained Models Contact I

Yuan Gong 603 Jan 07, 2023
[CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

Attention Helps CNN See Better: Hybrid Image Quality Assessment Network [CVPRW 2022] Code for Hybrid Image Quality Assessment Network [paper] [code] T

IIGROUP 49 Dec 11, 2022
Implementation of Invariant Point Attention, used for coordinate refinement in the structure module of Alphafold2, as a standalone Pytorch module

Invariant Point Attention - Pytorch Implementation of Invariant Point Attention as a standalone module, which was used in the structure module of Alph

Phil Wang 113 Jan 05, 2023
SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging.

SweiNet SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging. SweiNet takes as in

Felix Jin 3 Mar 31, 2022
SMD-Nets: Stereo Mixture Density Networks

SMD-Nets: Stereo Mixture Density Networks This repository contains a Pytorch implementation of "SMD-Nets: Stereo Mixture Density Networks" (CVPR 2021)

Fabio Tosi 115 Dec 26, 2022
Poisson Surface Reconstruction for LiDAR Odometry and Mapping

Poisson Surface Reconstruction for LiDAR Odometry and Mapping Surfels TSDF Our Approach Table: Qualitative comparison between the different mapping te

Photogrammetry & Robotics Bonn 305 Dec 21, 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks

This package requires jax, tensorflow, and numpy. Either tensorflow or scikit-learn can be used for loading data. To run in a nix-shell with required

Felix Biggs 0 Feb 04, 2022
HAT: Hierarchical Aggregation Transformers for Person Re-identification

HAT: Hierarchical Aggregation Transformers for Person Re-identification

11 Sep 05, 2022
A simple tutoral for error correction task, based on Pytorch

gramcorrector A simple tutoral for error correction task, based on Pytorch Grammatical Error Detection (sentence-level) a binary sequence-based classi

peiyuan_gong 8 Dec 03, 2022
Continuum Learning with GEM: Gradient Episodic Memory

Gradient Episodic Memory for Continual Learning Source code for the paper: @inproceedings{GradientEpisodicMemory, title={Gradient Episodic Memory

Facebook Research 360 Dec 27, 2022
Dynamical movement primitives (DMPs), probabilistic movement primitives (ProMPs), spatially coupled bimanual DMPs.

Movement Primitives Movement primitives are a common group of policy representations in robotics. There are many different types and variations. This

DFKI Robotics Innovation Center 63 Jan 06, 2023
Anomaly Detection Based on Hierarchical Clustering of Mobile Robot Data

We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for

Zekeriyya Demirci 1 Jan 09, 2022