Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2002.04806
Cited By
The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2020
12 February 2020
T. Sejnowski
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence"
50 / 69 papers shown
Morphological Cognition: Classifying MNIST Digits Through Morphological Computation Alone
Alican Mertan
Nick Cheney
123
0
0
24 Aug 2025
Embodied Intelligence: The Key to Unblocking Generalized Artificial Intelligence
Jinhao Jiang
Changlin Chen
Shile Feng
Wanru Geng
Zesheng Zhou
Ni Wang
Shuai Li
Feng-Qi Cui
Erbao Dong
AI4CE
318
2
0
11 May 2025
Tangentially Aligned Integrated Gradients for User-Friendly Explanations
Irish Conference on Artificial Intelligence and Cognitive Science (AICS), 2025
Lachlan Simpson
Federico Costanza
Kyle Millar
A. Cheng
Cheng-Chew Lim
Hong-Gunn Chew
FAtt
373
5
0
11 Mar 2025
On Space Folds of ReLU Neural Networks
Michal Lewandowski
Hamid Eghbalzadeh
Bernhard Heinzl
Raphael Pisoni
Bernhard A.Moser
MLT
482
3
0
17 Feb 2025
Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification
Ashim Dahal
Saydul Akbar Murad
Nick Rahimi
508
1
0
27 Jan 2025
A Self-attention Residual Convolutional Neural Network for Health Condition Classification of Cow Teat Images
Minghao Wang
105
0
0
30 Sep 2024
Supervised Learning Model for Key Frame Identification from Cow Teat Videos
Minghao Wang
Pinxue Lin
108
2
0
26 Sep 2024
Novel Saliency Analysis for the Forward Forward Algorithm
Mitra Bakhshi
302
2
0
18 Sep 2024
Algebraic Adversarial Attacks on Integrated Gradients
Lachlan Simpson
Federico Costanza
Kyle Millar
A. Cheng
Cheng-Chew Lim
Hong-Gunn Chew
SILM
AAML
532
4
0
23 Jul 2024
Trustworthy Artificial Intelligence in the Context of Metrology
Tameem Adel
Sam Bilson
Mark Levene
Andrew Thompson
196
7
0
14 Jun 2024
Probabilistic Lipschitzness and the Stable Rank for Comparing Explanation Models
Lachlan Simpson
Kyle Millar
A. Cheng
Cheng-Chew Lim
Hong-Gunn Chew
BDL
FAtt
351
3
0
29 Feb 2024
On the Role of Initialization on the Implicit Bias in Deep Linear Networks
Oria Gruber
H. Avron
AI4CE
193
1
0
04 Feb 2024
Deep Continuous Networks
Nergis Tomen
S. Pintea
Jan van Gemert
426
15
0
02 Feb 2024
The twin peaks of learning neural networks
Elizaveta Demyanenko
Christoph Feinauer
Enrico M. Malatesta
Luca Saglietti
325
0
0
23 Jan 2024
A Comprehensive Study of Vision Transformers in Image Classification Tasks
Mahmoud Khalil
Ahmad Khalil
A. Ngom
ViT
299
22
0
02 Dec 2023
Deep Neural Networks for Automatic Speaker Recognition Do Not Learn Supra-Segmental Temporal Features
Pattern Recognition Letters (PR), 2023
Daniel Neururer
Volker Dellwo
Thilo Stadelmann
367
4
0
01 Nov 2023
Differentiable Boustrophedon Paths That Enable Optimization Via Gradient Descent
IEEE International Conference on Robotics and Automation (ICRA), 2023
Thomas Manzini
Robin Murphy
172
2
0
18 Sep 2023
Generative AI
Business & Information Systems Engineering (BISE), 2023
Stefan Feuerriegel
Jochen Hartmann
Christian Janiesch
Patrick Zschech
411
1,257
0
13 Sep 2023
Math Agents: Computational Infrastructure, Mathematical Embedding, and Genomics
M. Swan
Takashi Kido
Eric Roland
R. P. D. Santos
AI4CE
286
21
0
04 Jul 2023
A Framework for Provably Stable and Consistent Training of Deep Feedforward Networks
Arunselvan Ramaswamy
S. Bhatnagar
Naman Saxena
143
1
0
20 May 2023
Few Shot Learning for Medical Imaging: A Comparative Analysis of Methodologies and Formal Mathematical Framework
Jannatul Nayem
Sayed Sahriar Hasan
Noshin Amina
Bristy Das
Md. Shahin Ali
M. Ahsan
S. Raman
417
18
0
08 May 2023
MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosis
Ling Yang
Shuihua Wang
Yudong Zhang
282
0
0
25 Apr 2023
Structural Neural Additive Models: Enhanced Interpretable Machine Learning
Mattias Luber
Anton Thielmann
Benjamin Säfken
259
11
0
18 Feb 2023
Annotated History of Modern AI and Deep Learning
Juergen Schmidhuber
MLAU
AI4TS
AI4CE
567
49
0
21 Dec 2022
Hebbian Deep Learning Without Feedback
International Conference on Learning Representations (ICLR), 2022
Adrien Journé
Hector Garcia Rodriguez
Qinghai Guo
Timoleon Moraitis
AAML
340
77
0
23 Sep 2022
Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks
David Oniani
Sonish Sivarajkumar
Yanshan Wang
223
5
0
31 Aug 2022
Gaussian Process Surrogate Models for Neural Networks
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Michael Y. Li
Erin Grant
Thomas Griffiths
BDL
SyDa
360
10
0
11 Aug 2022
Large Language Models and the Reverse Turing Test
Neural Computation (Neural Comput.), 2022
T. Sejnowski
ELM
733
143
0
28 Jul 2022
The Mean Dimension of Neural Networks -- What causes the interaction effects?
Roman Hahn
Christoph Feinauer
E. Borgonovo
FAtt
251
2
0
11 Jul 2022
Should attention be all we need? The epistemic and ethical implications of unification in machine learning
Conference on Fairness, Accountability and Transparency (FAccT), 2022
N. Fishman
Leif Hancox-Li
302
12
0
09 May 2022
An Empirical Study of the Occurrence of Heavy-Tails in Training a ReLU Gate
Sayar Karmakar
Anirbit Mukherjee
176
0
0
26 Apr 2022
A Theory of Natural Intelligence
C. Malsburg
Thilo Stadelmann
Benjamin Grewe
133
5
0
22 Apr 2022
Machine Learning and Deep Learning -- A review for Ecologists
Methods in Ecology and Evolution (Methods Ecol. Evol.), 2022
Maximilian Pichler
F. Hartig
479
271
0
11 Apr 2022
On the link between conscious function and general intelligence in humans and machines
Arthur Juliani
Kai Arulkumaran
Shuntaro Sasai
Ryota Kanai
413
28
0
24 Mar 2022
One Network Doesn't Rule Them All: Moving Beyond Handcrafted Architectures in Self-Supervised Learning
Sharath Girish
Debadeepta Dey
Neel Joshi
Vibhav Vineet
S. Shah
C. C. T. Mendes
Abhinav Shrivastava
Yale Song
SSL
267
2
0
15 Mar 2022
P2M: A Processing-in-Pixel-in-Memory Paradigm for Resource-Constrained TinyML Applications
Scientific Reports (Sci Rep), 2022
Gourav Datta
Souvik Kundu
Zihan Yin
R. T. Lakkireddy
Joe Mathai
A. Jacob
Peter A. Beerel
Akhilesh R. Jaiswal
295
50
0
07 Mar 2022
An Analytical Approach to Compute the Exact Preimage of Feed-Forward Neural Networks
Théo Nancy
Vassili Maillet
Johann Barbier
FAtt
183
0
0
28 Feb 2022
Scalable Geometric Deep Learning on Molecular Graphs
Nathan C. Frey
S. Samsi
Joseph McDonald
Lin Li
Connor W. Coley
V. Gadepally
GNN
AI4CE
163
4
0
06 Dec 2021
Leveraging The Topological Consistencies of Learning in Deep Neural Networks
Stuart Synakowski
Fabian Benitez-Quiroz
Aleix M. Martinez
140
0
0
30 Nov 2021
Embed Everything: A Method for Efficiently Co-Embedding Multi-Modal Spaces
Sarah Di
Robin Yu
Amol Kapoor
116
0
0
09 Oct 2021
Towards a theory of out-of-distribution learning
Jayanta Dey
Ali Geisa
Ronak D. Mehta
Tyler M. Tomita
Hayden S. Helm
Haoyin Xu
Eric Eaton
Jeffery Dick
Carey E. Priebe
Joshua T. Vogelstein
OOD
431
21
0
29 Sep 2021
Task Guided Compositional Representation Learning for ZDA
Shuang Liu
Mete Ozay
OOD
241
0
0
13 Sep 2021
Unified Regularity Measures for Sample-wise Learning and Generalization
Chi Zhang
Xiaoning Ma
Yu Liu
Le Wang
Yuanqi Su
Yuehu Liu
289
5
0
09 Aug 2021
SoftHebb: Bayesian Inference in Unsupervised Hebbian Soft Winner-Take-All Networks
Timoleon Moraitis
Dmitry Toichkin
Adrien Journé
Yansong Chua
Qinghai Guo
AAML
BDL
511
42
0
12 Jul 2021
Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise
Nidhin Harilal
Udit Bhatia
A. Ganguly
OOD
154
0
0
23 Jun 2021
Optimized ensemble deep learning framework for scalable forecasting of dynamics containing extreme events
Chaos (Chaos), 2021
Arnob Ray
Tanujit Chakraborty
D. Ghosh
AI4TS
219
34
0
09 Jun 2021
Physics-informed attention-based neural network for solving non-linear partial differential equations
R. Torrado
Pablo Ruiz
L. Cueto‐Felgueroso
M. Green
Tyler Friesen
S. Matringe
Julian Togelius
PINN
176
14
0
17 May 2021
Abstraction, Validation, and Generalization for Explainable Artificial Intelligence
Applied AI Letters (AA), 2021
Scott Cheng-Hsin Yang
Tomas Folke
Patrick Shafto
215
7
0
16 May 2021
A brain basis of dynamical intelligence for AI and computational neuroscience
J. Monaco
Kanaka Rajan
Grace M. Hwang
AI4CE
231
7
0
15 May 2021
Demystification of Few-shot and One-shot Learning
IEEE International Joint Conference on Neural Network (IJCNN), 2021
I. Tyukin
A. Gorban
Muhammad H. Alkhudaydi
Qinghua Zhou
177
19
0
25 Apr 2021
1
2
Next
Page 1 of 2
