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A high-bias, low-variance introduction to Machine Learning for
  physicists

A high-bias, low-variance introduction to Machine Learning for physicists

23 March 2018
Pankaj Mehta
Marin Bukov
Ching-Hao Wang
A. G. Day
C. Richardson
Charles K. Fisher
D. Schwab
    AI4CE
ArXivPDFHTML

Papers citing "A high-bias, low-variance introduction to Machine Learning for physicists"

49 / 49 papers shown
Title
Inferring genotype-phenotype maps using attention models
Inferring genotype-phenotype maps using attention models
Krishna Rijal
Caroline M. Holmes
Samantha Petti
Gautam Reddy
Michael M. Desai
Pankaj Mehta
22
0
0
14 Apr 2025
Machine learning for cerebral blood vessels' malformations
Machine learning for cerebral blood vessels' malformations
Irem Topal
Alexander Cherevko
Yuri Bugay
Maxim Shishlenin
Jean Barbier
Deniz Eroglu
Édgar Roldán
Roman Belousov
76
0
0
25 Nov 2024
Persistent Homology for Structural Characterization in Disordered Systems
Persistent Homology for Structural Characterization in Disordered Systems
An Wang
Li Zou
76
1
0
21 Nov 2024
Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC
Machine-Learning Analysis of Radiative Decays to Dark Matter at the LHC
E. Arganda
Marcela Carena
M. D. L. Rios
A. D. Perez
Duncan Rocha
Rosa María Sandá Seoane
Carlos E. M. Wagner
AI4CE
28
0
0
17 Oct 2024
A convolutional neural network approach to deblending seismic data
A convolutional neural network approach to deblending seismic data
Jing Sun
S. Slang
T. Elboth
Thomas Larsen Greiner
S. McDonald
L. Gelius
22
51
0
12 Sep 2024
Extreme time extrapolation capabilities and thermodynamic consistency of
  physics-inspired Neural Networks for the 3D microstructure evolution of
  materials
Extreme time extrapolation capabilities and thermodynamic consistency of physics-inspired Neural Networks for the 3D microstructure evolution of materials
Daniel Lanzoni
Andrea Fantasia
R. Bergamaschini
Olivier Pierre-Louis
F. Montalenti
AI4CE
29
0
0
29 Jul 2024
Predictive Coding Networks and Inference Learning: Tutorial and Survey
Predictive Coding Networks and Inference Learning: Tutorial and Survey
B. V. Zwol
Ro Jefferson
E. V. D. Broek
55
0
0
04 Jul 2024
Generative modeling through internal high-dimensional chaotic activity
Generative modeling through internal high-dimensional chaotic activity
Samantha J. Fournier
Pierfrancesco Urbani
32
1
0
17 May 2024
Statistical Mechanics and Artificial Neural Networks: Principles,
  Models, and Applications
Statistical Mechanics and Artificial Neural Networks: Principles, Models, and Applications
Lucas Böttcher
Gregory R. Wheeler
32
0
0
05 Apr 2024
Individual Text Corpora Predict Openness, Interests, Knowledge and Level
  of Education
Individual Text Corpora Predict Openness, Interests, Knowledge and Level of Education
M. Hofmann
M. T. Jansen
Christoph Wigbels
Benny B. Briesemeister
A. M. Jacobs
30
0
0
29 Mar 2024
Nonlinearity Enhanced Adaptive Activation Functions
Nonlinearity Enhanced Adaptive Activation Functions
David Yevick
25
1
0
29 Mar 2024
Convolutional Neural Networks for signal detection in real LIGO data
Convolutional Neural Networks for signal detection in real LIGO data
O. Zelenka
Bernd Brügmann
F. Ohme
32
2
0
12 Feb 2024
Machine learning in and out of equilibrium
Machine learning in and out of equilibrium
Shishir Adhikari
Alkan Kabakcciouglu
A. Strang
Deniz Yuret
M. Hinczewski
22
4
0
06 Jun 2023
Do deep neural networks have an inbuilt Occam's razor?
Do deep neural networks have an inbuilt Occam's razor?
Chris Mingard
Henry Rees
Guillermo Valle Pérez
A. Louis
UQCV
BDL
21
16
0
13 Apr 2023
Interpretable machine learning of amino acid patterns in proteins: a
  statistical ensemble approach
Interpretable machine learning of amino acid patterns in proteins: a statistical ensemble approach
A. Braghetto
E. Orlandini
M. Baiesi
40
4
0
27 Mar 2023
Tradeoff of generalization error in unsupervised learning
Tradeoff of generalization error in unsupervised learning
Gilhan Kim
Ho-Jun Lee
Junghyo Jo
Yongjoo Baek
13
0
0
10 Mar 2023
Noise-cleaning the precision matrix of fMRI time series
Noise-cleaning the precision matrix of fMRI time series
Miguel Ibánez-Berganza
C. Lucibello
Francesca Santucci
T. Gili
A. Gabrielli
32
1
0
06 Feb 2023
Galaxy Spin Classification I: Z-wise vs S-wise Spirals With Chirality
  Equivariant Residual Network
Galaxy Spin Classification I: Z-wise vs S-wise Spirals With Chirality Equivariant Residual Network
He Jia
Hong-Ming Zhu
U. Pen
17
5
0
09 Oct 2022
Machine learning algorithms for three-dimensional mean-curvature
  computation in the level-set method
Machine learning algorithms for three-dimensional mean-curvature computation in the level-set method
Luis Ángel Larios-Cárdenas
Frédéric Gibou
3DV
17
1
0
18 Aug 2022
Data Science and Machine Learning in Education
Data Science and Machine Learning in Education
G. Benelli
Thomas Y. Chen
Javier Mauricio Duarte
Matthew Feickert
Matthew Graham
...
K. Terao
S. Thais
A. Roy
J. Vlimant
G. Chachamis
AI4CE
26
5
0
19 Jul 2022
Residual-Concatenate Neural Network with Deep Regularization Layers for
  Binary Classification
Residual-Concatenate Neural Network with Deep Regularization Layers for Binary Classification
Abhishek Gupta
Sruthi Nair
Raunak Joshi
V. Chitre
23
5
0
25 May 2022
On Machine Learning-Driven Surrogates for Sound Transmission Loss
  Simulations
On Machine Learning-Driven Surrogates for Sound Transmission Loss Simulations
Barbara Z Cunha
A. Zine
M. Ichchou
C. Droz
Stéphane Foulard
AI4CE
30
4
0
25 Apr 2022
On the Dynamics of Inference and Learning
On the Dynamics of Inference and Learning
D. Berman
J. Heckman
Marc S. Klinger
21
10
0
19 Apr 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and
  Vibroacoustic
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic
Barbara Z Cunha
C. Droz
A. Zine
Stéphane Foulard
M. Ichchou
AI4CE
35
84
0
13 Apr 2022
A CNN based method for Sub-pixel Urban Land Cover Classification using
  Landsat-5 TM and Resourcesat-1 LISS-IV Imagery
A CNN based method for Sub-pixel Urban Land Cover Classification using Landsat-5 TM and Resourcesat-1 LISS-IV Imagery
Krishnadas Perikamana
K. Balakrishnan
Pratyush Tripathy
21
1
0
16 Dec 2021
Machine Learning in Nuclear Physics
Machine Learning in Nuclear Physics
A. Boehnlein
M. Diefenthaler
C. Fanelli
M. Hjorth-Jensen
T. Horn
...
M. Schram
A. Scheinker
Michael S. Smith
Xin-Nian Wang
Veronique Ziegler
AI4CE
37
41
0
04 Dec 2021
Extending the Relative Seriality Formalism for Interpretable Deep
  Learning of Normal Tissue Complication Probability Models
Extending the Relative Seriality Formalism for Interpretable Deep Learning of Normal Tissue Complication Probability Models
Tahir I Yusufaly
MedIm
11
0
0
25 Nov 2021
A comparative study of universal quantum computing models: towards a
  physical unification
A comparative study of universal quantum computing models: towards a physical unification
Dong-Sheng Wang
18
16
0
17 Aug 2021
The information of attribute uncertainties: what convolutional neural
  networks can learn about errors in input data
The information of attribute uncertainties: what convolutional neural networks can learn about errors in input data
Natália Villa Nova Rodrigues
L. Abramo
Nina Sumiko Tomita Hirata
18
6
0
10 Aug 2021
Unveiling the structure of wide flat minima in neural networks
Unveiling the structure of wide flat minima in neural networks
Carlo Baldassi
Clarissa Lauditi
Enrico M. Malatesta
Gabriele Perugini
R. Zecchina
16
32
0
02 Jul 2021
Flow-based sampling for fermionic lattice field theories
Flow-based sampling for fermionic lattice field theories
M. S. Albergo
G. Kanwar
S. Racanière
Danilo Jimenez Rezende
Julian M. Urban
D. Boyda
Kyle Cranmer
D. Hackett
P. Shanahan
AI4CE
15
43
0
10 Jun 2021
A hybrid inference system for improved curvature estimation in the
  level-set method using machine learning
A hybrid inference system for improved curvature estimation in the level-set method using machine learning
Luis Ángel Larios-Cárdenas
Frédéric Gibou
21
6
0
07 Apr 2021
Towards Understanding Ensemble, Knowledge Distillation and
  Self-Distillation in Deep Learning
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning
Zeyuan Allen-Zhu
Yuanzhi Li
FedML
58
355
0
17 Dec 2020
Memorizing without overfitting: Bias, variance, and interpolation in
  over-parameterized models
Memorizing without overfitting: Bias, variance, and interpolation in over-parameterized models
J. Rocks
Pankaj Mehta
18
41
0
26 Oct 2020
Machine learning for complete intersection Calabi-Yau manifolds: a
  methodological study
Machine learning for complete intersection Calabi-Yau manifolds: a methodological study
Harold Erbin
Riccardo Finotello
21
31
0
30 Jul 2020
Thermodynamic Machine Learning through Maximum Work Production
Thermodynamic Machine Learning through Maximum Work Production
A. B. Boyd
James P. Crutchfield
M. Gu
AI4CE
21
16
0
27 Jun 2020
CRYSPNet: Crystal Structure Predictions via Neural Network
CRYSPNet: Crystal Structure Predictions via Neural Network
Haotong Liang
V. Stanev
A. Kusne
Ichiro Takeuchi
19
37
0
31 Mar 2020
Single-exposure absorption imaging of ultracold atoms using deep
  learning
Single-exposure absorption imaging of ultracold atoms using deep learning
G. Ness
Anastasiya Vainbaum
Constantine Shkedrov
Yanay Florshaim
Y. Sagi
13
12
0
03 Mar 2020
A deep learning approach for the computation of curvature in the
  level-set method
A deep learning approach for the computation of curvature in the level-set method
Luis Ángel Larios-Cárdenas
Frédéric Gibou
13
14
0
04 Feb 2020
Learning the Ising Model with Generative Neural Networks
Learning the Ising Model with Generative Neural Networks
Francesco DÁngelo
Lucas Böttcher
AI4CE
16
28
0
15 Jan 2020
Optimizing quantum heuristics with meta-learning
Optimizing quantum heuristics with meta-learning
M. Wilson
Rachel Stromswold
Filip Wudarski
Stuart Hadfield
N. Tubman
E. Rieffel
11
74
0
08 Aug 2019
Parameterized quantum circuits as machine learning models
Parameterized quantum circuits as machine learning models
Marcello Benedetti
Erika Lloyd
Stefan H. Sack
Mattia Fiorentini
27
869
0
18 Jun 2019
Thermodynamics and Feature Extraction by Machine Learning
Thermodynamics and Feature Extraction by Machine Learning
S. Funai
D. Giataganas
DRL
AI4CE
16
34
0
18 Oct 2018
DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with
  Deep Neural Networks
DeepCMB: Lensing Reconstruction of the Cosmic Microwave Background with Deep Neural Networks
J. Caldeira
W. L. K. Wu
Brian D. Nord
Camille Avestruz
Shubhendu Trivedi
K. Story
25
63
0
02 Oct 2018
Towards Quantum Machine Learning with Tensor Networks
Towards Quantum Machine Learning with Tensor Networks
W. Huggins
P. Patil
K. B. Whaley
E. Stoudenmire
16
341
0
30 Mar 2018
First-order Methods Almost Always Avoid Saddle Points
First-order Methods Almost Always Avoid Saddle Points
J. Lee
Ioannis Panageas
Georgios Piliouras
Max Simchowitz
Michael I. Jordan
Benjamin Recht
ODL
93
82
0
20 Oct 2017
Flow Navigation by Smart Microswimmers via Reinforcement Learning
Flow Navigation by Smart Microswimmers via Reinforcement Learning
S. Colabrese
K. Gustavsson
A. Celani
Luca Biferale
33
156
0
30 Jan 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
308
2,890
0
15 Sep 2016
An algorithm for the principal component analysis of large data sets
An algorithm for the principal component analysis of large data sets
N. Halko
P. Martinsson
Y. Shkolnisky
M. Tygert
68
277
0
30 Jul 2010
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