Deep Learning for Classical Japanese Literature

3 December 2018

Papers citing "Deep Learning for Classical Japanese Literature"

50 / 145 papers shown

Title
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models Songsong Xiong Georgios Tziafas Hamidreza Kasaei ViT 31 3 0 03 Oct 2022
Analyzing Diffusion as Serial Reproduction Raja Marjieh Ilia Sucholutsky Thomas A. Langlois Nori Jacoby Thomas Griffiths DiffM 38 4 0 29 Sep 2022
Reduction from Complementary-Label Learning to Probability Estimates Weipeng Lin Hsuan-Tien Lin 35 9 0 20 Sep 2022
Wasserstein Task Embedding for Measuring Task Similarities Xinran Liu Yikun Bai Yuzhe Lu Andrea Soltoggio Soheil Kolouri OT 22 22 0 24 Aug 2022
Psychophysical Machine Learning B. N. Kausik 21 0 0 23 Aug 2022
ProPaLL: Probabilistic Partial Label Learning Lukasz Struski Jacek Tabor Bartosz Zieliñski 33 2 0 21 Aug 2022
Detection of Furigana Text in Images Nikolaj Kjoller Bjerregaard Dovile Juodelyte Stefan Heinrich 34 5 0 08 Jul 2022
Exact Spectral Norm Regularization for Neural Networks Anton Johansson Claes Strannegård Niklas Engsner P. Mostad AAML 25 2 0 27 Jun 2022
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning Javier Antorán David Janz J. Allingham Erik A. Daxberger Riccardo Barbano Eric T. Nalisnick José Miguel Hernández-Lobato UQCV BDL 37 28 0 17 Jun 2022
Adversarial Reprogramming Revisited Matthias Englert R. Lazic AAML 29 9 0 07 Jun 2022
TriBYOL: Triplet BYOL for Self-Supervised Representation Learning Guang Li Ren Togo Takahiro Ogawa Miki Haseyama SSL 21 17 0 07 Jun 2022
Drawing out of Distribution with Neuro-Symbolic Generative Models Yi-Chuan Liang J. Tenenbaum T. Le N. Siddharth 23 7 0 03 Jun 2022
muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems Andrea Gesmundo J. Dean 36 19 0 22 May 2022
Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies Alon Berliner Guy Rotman Yossi Adi Roi Reichart Tamir Hazan BDL DRL 26 4 0 03 May 2022
Uniform Manifold Approximation with Two-phase Optimization Hyeon Jeon Hyung-Kwon Ko S. Lee Jaemin Jo Jinwook Seo 37 13 0 01 May 2022
PR-DAD: Phase Retrieval Using Deep Auto-Decoders Leonid Gugel S. Dekel 17 0 0 18 Apr 2022
Decompositional Generation Process for Instance-Dependent Partial Label Learning Congyu Qiao Ning Xu Xin Geng 126 76 0 08 Apr 2022
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters Paul Gavrikov J. Keuper AAML 24 31 0 29 Mar 2022
Meta Mirror Descent: Optimiser Learning for Fast Convergence Boyan Gao Henry Gouk Haebeom Lee Timothy M. Hospedales 27 6 0 05 Mar 2022
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior Javier Antorán Riccardo Barbano Johannes Leuschner José Miguel Hernández-Lobato Bangti Jin UQCV 45 10 0 28 Feb 2022
Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization Weijia Zhang Xuanhui Zhang Hanwen Deng Min-Ling Zhang 21 22 0 25 Feb 2022
Activation Functions: Dive into an optimal activation function V. Bansal FAtt 29 2 0 24 Feb 2022
Development and Comparison of Scoring Functions in Curriculum Learning Himmet Toprak Kesgin M. Fatih Amasyali 27 3 0 10 Feb 2022
Controlling the Complexity and Lipschitz Constant improves polynomial nets Zhenyu Zhu Fabian Latorre Grigorios G. Chrysos V. Cevher 27 10 0 10 Feb 2022
Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks Lang Liu M. M. Fard Sen Zhao OOD 31 3 0 04 Feb 2022
DearFSAC: An Approach to Optimizing Unreliable Federated Learning via Deep Reinforcement Learning Chenghao Huang Weilong Chen Yuxi Chen Shunji Yang Yanru Zhang FedML 24 2 0 30 Jan 2022
OmniPrint: A Configurable Printed Character Synthesizer Haozhe Sun Wei-Wei Tu Isabelle M Guyon SyDa 46 7 0 17 Jan 2022
Problem-dependent attention and effort in neural networks with applications to image resolution and model selection Chris Rohlfs 34 4 0 05 Jan 2022
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback Boxin Zhao Lingxiao Wang Mladen Kolar Ziqi Liu Qing Cui Jun Zhou Chaochao Chen FedML 41 10 0 28 Dec 2021
Over-the-Air Federated Multi-Task Learning Over MIMO Multiple Access Channels Chen Zhong Huiyuan Yang Xiaojun Yuan 40 28 0 27 Dec 2021
Learning with Proper Partial Labels Zheng Wu Jiaqi Lv Masashi Sugiyama 26 8 0 23 Dec 2021
Importance of Kernel Bandwidth in Quantum Machine Learning Ruslan Shaydulin Stefan M. Wild 42 38 0 09 Nov 2021
Dynamic Inference with Neural Interpreters Nasim Rahaman Muhammad Waleed Gondal S. Joshi Peter V. Gehler Yoshua Bengio Francesco Locatello Bernhard Schölkopf 51 31 0 12 Oct 2021
Unsupervised Continual Learning in Streaming Environments Andri Ashfahani Mahardhika Pratama 17 21 0 20 Sep 2021
Evolving Architectures with Gradient Misalignment toward Low Adversarial Transferability K. Operiano W. Pora H. Iba Hiroshi Kera AAML 42 1 0 13 Sep 2021
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained Federated Learning with Heterogeneous On-Device Models Lan Zhang Dapeng Wu Xiaoyong Yuan FedML 38 48 0 08 Sep 2021
Deep Dive into Semi-Supervised ELBO for Improving Classification Performance Fahim Faisal Niloy M. A. Amin A. K. M. Mahbubur Rahman A. Ali DRL 30 0 0 29 Aug 2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing Tomas Geffner Justin Domke 33 34 0 08 Jul 2021
Graceful Degradation and Related Fields J. Dymond 33 4 0 21 Jun 2021
Non-Iterative Phase Retrieval With Cascaded Neural Networks Tobias Uelwer Tobias Hoffmann Stefan Harmeling 29 11 0 18 Jun 2021
Being a Bit Frequentist Improves Bayesian Neural Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 23 15 0 18 Jun 2021
Multi-Class Classification from Single-Class Data with Confidences Yuzhou Cao Lei Feng Senlin Shu Yitian Xu Bo An Gang Niu Masashi Sugiyama 19 3 0 16 Jun 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective Akhilan Boopathy Ila Fiete 44 9 0 15 Jun 2021
Robust Out-of-Distribution Detection on Deep Probabilistic Generative Models Jaemoo Choi Changyeon Yoon Jeongwoo Bae Myung-joo Kang OODD 30 4 0 15 Jun 2021
Leveraged Weighted Loss for Partial Label Learning Hongwei Wen Jingyi Cui H. Hang Jiabin Liu Yisen Wang Zhouchen Lin 16 95 0 10 Jun 2021
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions Ameya Dilip Jagtap Yeonjong Shin Kenji Kawaguchi George Karniadakis ODL 45 131 0 20 May 2021
MOOD: Multi-level Out-of-distribution Detection Ziqian Lin Sreya . Dutta Roy Yixuan Li OODD 34 114 0 30 Apr 2021
Searching for Robustness: Loss Learning for Noisy Classification Tasks Boyan Gao Henry Gouk Timothy M. Hospedales OOD NoLa 36 18 0 27 Feb 2021
A statistical framework for efficient out of distribution detection in deep neural networks Matan Haroush Tzviel Frostig R. Heller Daniel Soudry OODD 25 37 0 25 Feb 2021
Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques Filip Hanzely Boxin Zhao Mladen Kolar FedML 34 53 0 19 Feb 2021