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On the Reproducibility of Neural Network Predictions

On the Reproducibility of Neural Network Predictions

5 February 2021
Srinadh Bhojanapalli
Kimberly Wilber
Andreas Veit
A. S. Rawat
Seungyeon Kim
A. Menon
Sanjiv Kumar
ArXivPDFHTML

Papers citing "On the Reproducibility of Neural Network Predictions"

24 / 24 papers shown
Title
Exponential Moving Average of Weights in Deep Learning: Dynamics and
  Benefits
Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits
Daniel Morales-Brotons
Thijs Vogels
Hadrien Hendrikx
123
17
0
27 Nov 2024
Distilling Influences to Mitigate Prediction Churn in Graph Neural
  Networks
Distilling Influences to Mitigate Prediction Churn in Graph Neural Networks
Andreas Roth
Thomas Liebig
52
0
0
02 Oct 2023
Transferring Learning Trajectories of Neural Networks
Transferring Learning Trajectories of Neural Networks
Daiki Chijiwa
25
2
0
23 May 2023
Measuring and Mitigating Local Instability in Deep Neural Networks
Measuring and Mitigating Local Instability in Deep Neural Networks
Arghya Datta
Subhrangshu Nandi
Jingcheng Xu
Greg Ver Steeg
He Xie
Anoop Kumar
Aram Galstyan
20
3
0
18 May 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Max Klabunde
Tobias Schumacher
M. Strohmaier
Florian Lemmerich
52
64
0
10 May 2023
Maintaining Stability and Plasticity for Predictive Churn Reduction
Maintaining Stability and Plasticity for Predictive Churn Reduction
George Adam
B. Haibe-Kains
Anna Goldenberg
23
1
0
06 May 2023
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks
  with Soft-Thresholding
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding
Chunyan Xiong
Meng Lu
Xiaotong Yu
JIAN-PENG Cao
Zhong Chen
D. Guo
X. Qu
MLT
37
0
0
14 Apr 2023
On the Variance of Neural Network Training with respect to Test Sets and
  Distributions
On the Variance of Neural Network Training with respect to Test Sets and Distributions
Keller Jordan
OOD
21
10
0
04 Apr 2023
Measuring the Instability of Fine-Tuning
Measuring the Instability of Fine-Tuning
Yupei Du
D. Nguyen
25
4
0
15 Feb 2023
On the Factory Floor: ML Engineering for Industrial-Scale Ads
  Recommendation Models
On the Factory Floor: ML Engineering for Industrial-Scale Ads Recommendation Models
Rohan Anil
S. Gadanho
Danya Huang
Nijith Jacob
Zhuoshu Li
...
Cristina Pop
Kevin Regan
G. Shamir
Rakesh Shivanna
Qiqi Yan
3DV
26
41
0
12 Sep 2022
Quantifying Inherent Randomness in Machine Learning Algorithms
Quantifying Inherent Randomness in Machine Learning Algorithms
Soham Raste
Rahul Singh
J. Vaughan
V. Nair
44
9
0
24 Jun 2022
On the Prediction Instability of Graph Neural Networks
On the Prediction Instability of Graph Neural Networks
Max Klabunde
Florian Lemmerich
40
5
0
20 May 2022
Predicting on the Edge: Identifying Where a Larger Model Does Better
Predicting on the Edge: Identifying Where a Larger Model Does Better
Taman Narayan
Heinrich Jiang
Sen Zhao
Surinder Kumar
25
7
0
15 Feb 2022
Real World Large Scale Recommendation Systems Reproducibility and Smooth
  Activations
Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations
G. Shamir
Dong Lin
HAI
OffRL
25
6
0
14 Feb 2022
Reproducibility in Optimization: Theoretical Framework and Limits
Reproducibility in Optimization: Theoretical Framework and Limits
Kwangjun Ahn
Prateek Jain
Ziwei Ji
Satyen Kale
Praneeth Netrapalli
G. Shamir
22
22
0
09 Feb 2022
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
Aaron Mishkin
Arda Sahiner
Mert Pilanci
OffRL
77
30
0
02 Feb 2022
Neural Network Weights Do Not Converge to Stationary Points: An
  Invariant Measure Perspective
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective
Junzhe Zhang
Haochuan Li
S. Sra
Ali Jadbabaie
66
9
0
12 Oct 2021
Use of speaker recognition approaches for learning and evaluating
  embedding representations of musical instrument sounds
Use of speaker recognition approaches for learning and evaluating embedding representations of musical instrument sounds
Xuan Shi
Erica Cooper
Junichi Yamagishi
24
7
0
24 Jul 2021
Assessing Generalization of SGD via Disagreement
Assessing Generalization of SGD via Disagreement
Yiding Jiang
Vaishnavh Nagarajan
Christina Baek
J. Zico Kolter
61
108
0
25 Jun 2021
Churn Reduction via Distillation
Churn Reduction via Distillation
Heinrich Jiang
Harikrishna Narasimhan
Dara Bahri
Andrew Cotter
Afshin Rostamizadeh
27
15
0
04 Jun 2021
Synthesizing Irreproducibility in Deep Networks
Synthesizing Irreproducibility in Deep Networks
R. Snapp
G. Shamir
OOD
24
10
0
21 Feb 2021
Knowledge Distillation by On-the-Fly Native Ensemble
Knowledge Distillation by On-the-Fly Native Ensemble
Xu Lan
Xiatian Zhu
S. Gong
192
473
0
12 Jun 2018
Large scale distributed neural network training through online
  distillation
Large scale distributed neural network training through online distillation
Rohan Anil
Gabriel Pereyra
Alexandre Passos
Róbert Ormándi
George E. Dahl
Geoffrey E. Hinton
FedML
278
404
0
09 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
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