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1704.00109
Cited By
Snapshot Ensembles: Train 1, get M for free
1 April 2017
Gao Huang
Yixuan Li
Geoff Pleiss
Zhuang Liu
J. Hopcroft
Kilian Q. Weinberger
OOD
FedML
UQCV
Re-assign community
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Papers citing
"Snapshot Ensembles: Train 1, get M for free"
50 / 441 papers shown
Title
Concepts and Applications of Conformal Prediction in Computational Drug Discovery
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Mingsheng Long
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Sound source detection, localization and classification using consecutive ensemble of CRNN models
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Improving Malaria Parasite Detection from Red Blood Cell using Deep Convolutional Neural Networks
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H. Zunair
Mohammad Sohel Rahman
Jesia Quader Yuki
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Md. Ashraful Alam
N. Alam
M. Mahdy
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57
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Classification of Macromolecule Type Based on Sequences of Amino Acids Using Deep Learning
Sarwar Khan
F. Ghaffar
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Random Vector Functional Link Neural Network based Ensemble Deep Learning
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Homogeneous Vector Capsules Enable Adaptive Gradient Descent in Convolutional Neural Networks
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T. Kalganova
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7
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Large Scale Structure of Neural Network Loss Landscapes
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Stanislaw Jastrzebski
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Training Data Subset Search with Ensemble Active Learning
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J. Álvarez
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14
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Augmenting correlation structures in spatial data using deep generative models
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Adriano Soares Koshiyama
Sebastian Flennerhag
19
21
0
23 May 2019
Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network
Oscar Chang
Yuling Yao
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29
8
0
23 May 2019
Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints
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Ersin Yumer
Deva Ramanan
12
46
0
12 May 2019
Learning Representations for Predicting Future Activities
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Özgün Çiçek
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AI4TS
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An Ensemble of Epoch-wise Empirical Bayes for Few-shot Learning
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Bernt Schiele
Qianru Sun
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25
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G
\mathcal{G}
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30
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11
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Chunyuan Li
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359
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Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs
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6
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0
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11
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11
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Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
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Chunyuan Li
Jianyi Zhang
Changyou Chen
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Artificial Intelligence for Prosthetics - challenge solutions
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Sean F. Carroll
...
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Scott L. Delp
13
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0
07 Feb 2019
Asymmetric Valleys: Beyond Sharp and Flat Local Minima
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Yang Yuan
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12
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ECG Segmentation by Neural Networks: Errors and Correction
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A. Koneva
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21
27
0
26 Dec 2018
AVRA: Automatic Visual Ratings of Atrophy from MRI images using Recurrent Convolutional Neural Networks
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D. Ferreira
L. Cavallin
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Chunliang Wang
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25
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Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth
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19
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Proximal Mean-field for Neural Network Quantization
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P. Dokania
Richard I. Hartley
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MQ
27
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11 Dec 2018
Channel selection using Gumbel Softmax
Charles Herrmann
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Ramin Zabih
15
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11 Dec 2018
Learning Transferable Adversarial Examples via Ghost Networks
Yingwei Li
S. Bai
Yuyin Zhou
Cihang Xie
Zhishuai Zhang
Alan Yuille
AAML
34
134
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MEAL: Multi-Model Ensemble via Adversarial Learning
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Xiangyang Xue
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17
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Cerebrovascular Network Segmentation on MRA Images with Deep Learning
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21
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Parameter Re-Initialization through Cyclical Batch Size Schedules
Norman Mu
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A. Gholami
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22
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Snapshot Distillation: Teacher-Student Optimization in One Generation
Chenglin Yang
Lingxi Xie
Chi Su
Alan Yuille
10
191
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Generalized Coarse-to-Fine Visual Recognition with Progressive Training
Xutong Ren
Lingxi Xie
Chen Wei
Siyuan Qiao
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Jiaying Liu
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Elliot K. Fishman
Alan Yuille
ObjD
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29 Nov 2018
Regularizing by the Variance of the Activations' Sample-Variances
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Lior Wolf
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12
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A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural Networks
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6
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Self-Referenced Deep Learning
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19
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Sharpen Focus: Learning with Attention Separability and Consistency
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14
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A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
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Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks
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A. Bender
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9
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Synthetic Occlusion Augmentation with Volumetric Heatmaps for the 2018 ECCV PoseTrack Challenge on 3D Human Pose Estimation
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MotherNets: Rapid Deep Ensemble Learning
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Stratos Idreos
6
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Learning to Support: Exploiting Structure Information in Support Sets for One-Shot Learning
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S. Gibson
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26
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Don't Use Large Mini-Batches, Use Local SGD
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Kumar Kshitij Patel
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25
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Testing the Efficient Network TRaining (ENTR) Hypothesis: initially reducing training image size makes Convolutional Neural Network training for image recognition tasks more efficient
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15
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A Deep Learning Driven Active Framework for Segmentation of Large 3D Shape Collections
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Yu-Kun Lai
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