文件名称：Machine-Learning-Research-Papers:机器学习、深度学习及相关领域的研究论文列表
文件大小：2.27MB
文件格式：ZIP
更新时间：2024-06-19 14:39:21
machine-learning deep-learning awesome-list research-paper conference-paper
机器学习研究论文 机器学习、深度学习及相关领域的研究论文列表。 我整理了一份我遇到和阅读的研究论文清单。 我会在每周阅读论文时不断更新论文列表及其摘要。 如何阅读研究论文 Andrew Ng 教授就给出了一些很棒的技巧。 我在总结了提示。 目录 可以根据区分标准查看论文列表，例如（会议地点、出版年份、主题涵盖、作者等）。 以下过滤格式可用于查看论文列表： 所有论文 论文名称 地位 话题 类别 年 会议 作者 概括 关联 0 读 CNN、简历、图像 可视化 2014年 ECCV 马修·D·泽勒，罗伯·弗格斯 在 CNN 过滤器激活上使用反卷积可视化 CNN 过滤器/内核。 1 读 CNN、简历、图像 建筑学 2015年 CVPR 克里斯蒂安·塞格迪，刘伟 提出使用1x1 conv操作来减少深度和宽CNN中的参数数量 关联 2 ResNet（用于图像识别的深度残差学习） 读 C
【文件预览】：
Machine-Learning-Research-Papers-master
----.gitignore(110B)
----How_to_Read_Research_Papers.pdf(2.16MB)
----filtered_year_wise.md(50KB)
----filtered_read_and_summarised.md(9KB)
----Research_Papers_Anubhav_Reads()
--------StarGAN_Unified_Generative_Adversarial_Networks_fo.md(555B)
--------ResNet_Deep_Residual_Learning_for_Image_Recogniti.md(1KB)
--------Reformer_The_Efficient_Transformer.md(2KB)
--------The_Lottery_Ticket_Hypothesis_Finding_Sparse,_Trai.md(464B)
--------WGAN_Wasserstein_GAN.md(389B)
--------Attention_is_All_you_Need.md(1KB)
--------Occupancy_Anticipation_for_Efficient_Exploration_a.md(429B)
--------Topological_Loss_Beyond_the_Pixel-Wise_Loss_for_To.md(550B)
--------ZF_Net_Visualizing_and_Understanding_Convolutiona.md(1KB)
--------Cross-lingual_Language_Model_Pretraining.md(422B)
--------StyleGAN_A_Style-Based_Generator_Architecture_for_.md(552B)
--------IMLE-GAN_Inclusive_GAN_Improving_Data_and_Minority.md(661B)
--------Pix2Pix_Image-to-Image_Translation_with_Conditiona.md(1KB)
--------Word2Vec_Efficient_Estimation_of_Word_Representati.md(464B)
--------T5_Exploring_the_Limits_of_Transfer_Learning_with_.md(2KB)
--------BERT_Pre-training_of_Deep_Bidirectional_Transforme.md(1KB)
--------Progressive_Growing_of_GANs_for_Improved_Quality,_.md(465B)
--------Phrase-Based_&_Neural_Unsupervised_Machine_Transla.md(485B)
--------Perceptual_Losses_for_Real-Time_Style_Transfer_and.md(429B)
--------Bag_of_Tricks_for_Image_Classification_with_Convol.md(446B)
--------AnimeGAN_Towards_the_Automatic_Anime_Characters_Cr.md(443B)
--------Group_Normalization.md(384B)
--------Arbitrary_Style_Transfer_in_Real-Time_With_Adaptiv.md(484B)
--------SAGAN_Self-Attention_Generative_Adversarial_Networ.md(461B)
--------Class-Balanced_Loss_Based_on_Effective_Number_of_S.md(518B)
--------Pruning_Filters_for_Efficient_ConvNets.md(413B)
--------MobileNet_Efficient_Convolutional_Neural_Networks.md(483B)
--------All_you_need_is_a_good_init.md(397B)
--------Few-Shot_Learning_with_Localization_in_Realistic_S.md(545B)
--------Spectral_Normalization_for_GANs.md(440B)
--------Graph_Neural_Network_Relational_inductive_biases,_.md(474B)
--------Revisiting_Pose-Normalization_for_Fine-Grained_Few.md(572B)
--------One-shot_Text_Field_Labeling_using_Attention_and_B.md(474B)
--------Evaluation_of_neural_network_architectures_for_emb.md(1KB)
--------Approximating_CNNs_with_Bag-of-local-Features_mode.md(441B)
--------Image2StyleGAN_How_to_Embed_Images_Into_the_StyleG.md(530B)
--------Unsupervised_Machine_Translation_Using_Monolingual.md(500B)
--------How_Does_Batch_Normalization_Help_Optimization.md(459B)
--------A_Simple_yet_Effective_Baseline_for_3D_Human_Pose_.md(507B)
--------NADAM_Incorporating_Nesterov_Momentum_into_Adam.md(398B)
--------Single_Headed_Attention_RNN_Stop_Thinking_With_You.md(434B)
--------A_2019_guide_to_Human_Pose_Estimation_with_Deep_Le.md(447B)
--------Deep_Double_Descent_Where_Bigger_Models_and_More_D.md(449B)
--------SqueezeNet.md(1KB)
--------Breaking_neural_networks_with_adversarial_attacks.md(456B)
--------COMET_Commonsense_Transformers_for_Automatic_Knowl.md(403B)
--------Self-Normalizing_Neural_Networks.md(490B)
--------Improved_Techniques_for_Training_GANs.md(498B)
--------Language-Agnostic_BERT_Sentence_Embedding.md(2KB)
--------Untitled.md(203B)
--------Training_BatchNorm_and_Only_BatchNorm_On_the_Expre.md(451B)
--------GPT-f_Generative_Language_Modeling_for_Automated_T.md(227B)
--------ATOMIC_An_Atlas_of_Machine_Commonsense_for_If-Then.md(438B)
--------Inception-v1_Going_Deeper_With_Convolutions.md(978B)
--------Understanding_Loss_Functions_in_Computer_Vision.md(522B)
--------CycleGAN_Unpaired_Image-To-Image_Translation_Using.md(564B)
--------Capsule_Networks_Dynamic_Routing_Between_Capsules.md(434B)
--------MuZero_Mastering_Go,_chess,_shogi_and_Atari_withou.md(512B)
--------A_Comprehensive_Guide_on_Activation_Functions.md(444B)
--------Adam_A_Method_for_Stochastic_Optimization.md(385B)
--------VisualCOMET_Reasoning_about_the_Dynamic_Context_of.md(467B)
--------Vision_Transformer_An_Image_is_Worth_16x16_Words_T.md(295B)
--------GPT-2_Language_Models_are_Unsupervised_Multitask_.md(558B)
--------BEGAN_Boundary_Equilibrium_Generative_Adversarial_.md(414B)
----README.md(58KB)
----filtered_conference_wise.md(53KB)
----filtered_category_wise.md(58KB)
----filtered_topic_wise.md(116KB)
----filtered_author_wise.md(215KB)