狠狠撸shows by User: tmasada / http://www.slideshare.net/images/logo.gif 狠狠撸shows by User: tmasada / Fri, 15 Jul 2022 14:31:20 GMT 狠狠撸Share feed for 狠狠撸shows by User: tmasada Learning Latent Space Energy Based Prior Modelの解説 /slideshow/learning-latent-space-energy-based-prior-model-252194923/252194923 learninglatentspaceenergybasedpriormodel-220715143120-a9a338ef
Learning Latent Space Energy-Based Prior Model https://arxiv.org/abs/2006.08205 この論文の末尾に付いているPyTorch codeを理解できるようになるための解説です。]]>

Learning Latent Space Energy-Based Prior Model https://arxiv.org/abs/2006.08205 この論文の末尾に付いているPyTorch codeを理解できるようになるための解説です。]]>
Fri, 15 Jul 2022 14:31:20 GMT /slideshow/learning-latent-space-energy-based-prior-model-252194923/252194923 tmasada@slideshare.net(tmasada) Learning Latent Space Energy Based Prior Modelの解説 tmasada Learning Latent Space Energy-Based Prior Model https://arxiv.org/abs/2006.08205 この論文の末尾に付いているPyTorch codeを理解できるようになるための解説です。 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/learninglatentspaceenergybasedpriormodel-220715143120-a9a338ef-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Learning Latent Space Energy-Based Prior Model https://arxiv.org/abs/2006.08205 この論文の末尾に付いているPyTorch codeを理解できるようになるための解説です。
Learning Latent Space Energy Based Prior Modelの解説 from Tomonari Masada
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Denoising Diffusion Probabilistic Modelsの重要な式の解説 /slideshow/denoising-diffusion-probabilistic-models/238467087 memo20200913diffusionmodels-200913132644
Denoising Diffusion Probabilistic Modelsの重要な式の解説]]>

Denoising Diffusion Probabilistic Modelsの重要な式の解説]]>
Sun, 13 Sep 2020 13:26:44 GMT /slideshow/denoising-diffusion-probabilistic-models/238467087 tmasada@slideshare.net(tmasada) Denoising Diffusion Probabilistic Modelsの重要な式の解説 tmasada Denoising Diffusion Probabilistic Modelsの重要な式の解説 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/memo20200913diffusionmodels-200913132644-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Denoising Diffusion Probabilistic Modelsの重要な式の解説
Denoising Diffusion Probabilistic Modelsの重要な式の解説 from Tomonari Masada
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Context-dependent Token-wise Variational Autoencoder for Topic Modeling /tmasada/contextdependent-tokenwise-variational-autoencoder-for-topic-modeling kdweb2019paper1-190621104646
presented at KDWEB 2019 workshop ]]>

presented at KDWEB 2019 workshop ]]>
Fri, 21 Jun 2019 10:46:45 GMT /tmasada/contextdependent-tokenwise-variational-autoencoder-for-topic-modeling tmasada@slideshare.net(tmasada) Context-dependent Token-wise Variational Autoencoder for Topic Modeling tmasada presented at KDWEB 2019 workshop <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/kdweb2019paper1-190621104646-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> presented at KDWEB 2019 workshop
Context-dependent Token-wise Variational Autoencoder for Topic Modeling from Tomonari Masada
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A note on the density of Gumbel-softmax /slideshow/a-note-on-the-density-of-gumbelsoftmax/148079812 anoteonthedensityofgumbelsoftmax-190529061107
This note explicates some details of the discussion given in Appendix B of E. Jang, S. Gu, and B. Poole. Categorical representation with Gumbel-softmax. ICLR, 2017.]]>

This note explicates some details of the discussion given in Appendix B of E. Jang, S. Gu, and B. Poole. Categorical representation with Gumbel-softmax. ICLR, 2017.]]>
Wed, 29 May 2019 06:11:06 GMT /slideshow/a-note-on-the-density-of-gumbelsoftmax/148079812 tmasada@slideshare.net(tmasada) A note on the density of Gumbel-softmax tmasada This note explicates some details of the discussion given in Appendix B of E. Jang, S. Gu, and B. Poole. Categorical representation with Gumbel-softmax. ICLR, 2017. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/anoteonthedensityofgumbelsoftmax-190529061107-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> This note explicates some details of the discussion given in Appendix B of E. Jang, S. Gu, and B. Poole. Categorical representation with Gumbel-softmax. ICLR, 2017.
A note on the density of Gumbel-softmax from Tomonari Masada
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トピックモデルの基础と応用 /slideshow/ss-137943293/137943293 topicmodeling-190324150834
日本計算機統計学会 スタディーグループ 「IR(Institutional Research)のための統計的モデル構築に関する研究」ワークショップ 開催日時:2019年3月23日(土) 13:30~17:00 会場: 統計数理研究所 セミナー室1 ]]>

日本計算機統計学会 スタディーグループ 「IR(Institutional Research)のための統計的モデル構築に関する研究」ワークショップ 開催日時:2019年3月23日(土) 13:30~17:00 会場: 統計数理研究所 セミナー室1 ]]>
Sun, 24 Mar 2019 15:08:34 GMT /slideshow/ss-137943293/137943293 tmasada@slideshare.net(tmasada) トピックモデルの基础と応用 tmasada 日本計算機統計学会 スタディーグループ 「IR(Institutional Research)のための統計的モデル構築に関する研究」ワークショップ 開催日時:2019年3月23日(土) 13:30~17:00 会場: 統計数理研究所 セミナー室1 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/topicmodeling-190324150834-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> 日本計算機統計学会 スタディーグループ 「IR(Institutional Research)のための統計的モデル構築に関する研究」ワークショップ 開催日時:2019年3月23日(土) 13:30~17:00 会場: 統計数理研究所 セミナー室1
トピックモデルの基础と応用 from Tomonari Masada
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Expectation propagation for latent Dirichlet allocation /slideshow/expectation-propagation-for-latent-dirichlet-allocation/123683225 expectationpropagationforlatentdirichletallocation-181122064424
Expectation propagation for latent Dirichlet allocation This is a revised version of http://www.cis.nagasaki-u.ac.jp/~masada/2012121001.pdf]]>

Expectation propagation for latent Dirichlet allocation This is a revised version of http://www.cis.nagasaki-u.ac.jp/~masada/2012121001.pdf]]>
Thu, 22 Nov 2018 06:44:24 GMT /slideshow/expectation-propagation-for-latent-dirichlet-allocation/123683225 tmasada@slideshare.net(tmasada) Expectation propagation for latent Dirichlet allocation tmasada Expectation propagation for latent Dirichlet allocation This is a revised version of http://www.cis.nagasaki-u.ac.jp/~masada/2012121001.pdf <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/expectationpropagationforlatentdirichletallocation-181122064424-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Expectation propagation for latent Dirichlet allocation This is a revised version of http://www.cis.nagasaki-u.ac.jp/~masada/2012121001.pdf
Expectation propagation for latent Dirichlet allocation from Tomonari Masada
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Mini-batch Variational Inference for Time-Aware Topic Modeling /slideshow/minibatch-variational-inference-for-timeaware-topic-modeling/111291786 mypricai2018-180824082723
manuscript for review (accepted as poster paper for PRICAI 2018)]]>

manuscript for review (accepted as poster paper for PRICAI 2018)]]>
Fri, 24 Aug 2018 08:27:23 GMT /slideshow/minibatch-variational-inference-for-timeaware-topic-modeling/111291786 tmasada@slideshare.net(tmasada) Mini-batch Variational Inference for Time-Aware Topic Modeling tmasada manuscript for review (accepted as poster paper for PRICAI 2018) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mypricai2018-180824082723-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> manuscript for review (accepted as poster paper for PRICAI 2018)
Mini-batch Variational Inference for Time-Aware Topic Modeling from Tomonari Masada
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A note on variational inference for the univariate Gaussian /slideshow/a-note-on-variational-inference-for-the-univariate-gaussian/93425708 vb-univariate-gaussian-180410085735
cf. Sec. 10.1.3 of PRML by C. M. Bishop]]>

cf. Sec. 10.1.3 of PRML by C. M. Bishop]]>
Tue, 10 Apr 2018 08:57:35 GMT /slideshow/a-note-on-variational-inference-for-the-univariate-gaussian/93425708 tmasada@slideshare.net(tmasada) A note on variational inference for the univariate Gaussian tmasada cf. Sec. 10.1.3 of PRML by C. M. Bishop <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/vb-univariate-gaussian-180410085735-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> cf. Sec. 10.1.3 of PRML by C. M. Bishop
A note on variational inference for the univariate Gaussian from Tomonari Masada
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Document Modeling with Implicit Approximate Posterior Distributions /tmasada/document-modeling-with-implicit-approximate-posterior-distributions-92976979 myicdpa2018-180405144636
accepted for ICDPA 2018]]>

accepted for ICDPA 2018]]>
Thu, 05 Apr 2018 14:46:36 GMT /tmasada/document-modeling-with-implicit-approximate-posterior-distributions-92976979 tmasada@slideshare.net(tmasada) Document Modeling with Implicit Approximate Posterior Distributions tmasada accepted for ICDPA 2018 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/myicdpa2018-180405144636-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> accepted for ICDPA 2018
Document Modeling with Implicit Approximate Posterior Distributions from Tomonari Masada
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LDA-Based Scoring of Sequences Generated by RNN for Automatic Tanka Composition /slideshow/ldabased-scoring-of-sequences-generated-by-rnn-for-automatic-tanka-composition/92030032 iccs2018paper46-180327075437
manuscript for review (accepted as short paper for ICCS 2018)]]>

manuscript for review (accepted as short paper for ICCS 2018)]]>
Tue, 27 Mar 2018 07:54:37 GMT /slideshow/ldabased-scoring-of-sequences-generated-by-rnn-for-automatic-tanka-composition/92030032 tmasada@slideshare.net(tmasada) LDA-Based Scoring of Sequences Generated by RNN for Automatic Tanka Composition tmasada manuscript for review (accepted as short paper for ICCS 2018) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iccs2018paper46-180327075437-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> manuscript for review (accepted as short paper for ICCS 2018)
LDA-Based Scoring of Sequences Generated by RNN for Automatic Tanka Composition from Tomonari Masada
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A Note on ZINB-VAE /slideshow/a-note-on-zinbvae/79552716 note-zinb-vae-170908084836
https://arxiv.org/abs/1709.02082]]>

https://arxiv.org/abs/1709.02082]]>
Fri, 08 Sep 2017 08:48:36 GMT /slideshow/a-note-on-zinbvae/79552716 tmasada@slideshare.net(tmasada) A Note on ZINB-VAE tmasada https://arxiv.org/abs/1709.02082 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/note-zinb-vae-170908084836-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> https://arxiv.org/abs/1709.02082
A Note on ZINB-VAE from Tomonari Masada
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A Note on Latent LSTM Allocation /slideshow/a-note-on-latent-lstm-allocation/79276397 note-latent-lstm-170830070218
A Note on Latent LSTM Allocation http://proceedings.mlr.press/v70/zaheer17a.html]]>

A Note on Latent LSTM Allocation http://proceedings.mlr.press/v70/zaheer17a.html]]>
Wed, 30 Aug 2017 07:02:18 GMT /slideshow/a-note-on-latent-lstm-allocation/79276397 tmasada@slideshare.net(tmasada) A Note on Latent LSTM Allocation tmasada A Note on Latent LSTM Allocation http://proceedings.mlr.press/v70/zaheer17a.html <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/note-latent-lstm-170830070218-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A Note on Latent LSTM Allocation http://proceedings.mlr.press/v70/zaheer17a.html
A Note on Latent LSTM Allocation from Tomonari Masada
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A Note on TopicRNN /slideshow/a-note-on-topicrnn/77698983 note-topicrnn-170710100510
derivation of the lower bound to be maximized]]>

derivation of the lower bound to be maximized]]>
Mon, 10 Jul 2017 10:05:10 GMT /slideshow/a-note-on-topicrnn/77698983 tmasada@slideshare.net(tmasada) A Note on TopicRNN tmasada derivation of the lower bound to be maximized <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/note-topicrnn-170710100510-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> derivation of the lower bound to be maximized
A Note on TopicRNN from Tomonari Masada
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Topic modeling with Poisson factorization (2) /slideshow/topic-modeling-with-poisson-factorization-2/72891258 topic-modeling-poisson-170307081618
A modified version of the manuscript Published on Feb 3, 2017. 1. Use a gamma prior for $r_k$. 2. Use the same shape parameter $s$ for all gamma distributions.]]>

A modified version of the manuscript Published on Feb 3, 2017. 1. Use a gamma prior for $r_k$. 2. Use the same shape parameter $s$ for all gamma distributions.]]>
Tue, 07 Mar 2017 08:16:17 GMT /slideshow/topic-modeling-with-poisson-factorization-2/72891258 tmasada@slideshare.net(tmasada) Topic modeling with Poisson factorization (2) tmasada A modified version of the manuscript Published on Feb 3, 2017. 1. Use a gamma prior for $r_k$. 2. Use the same shape parameter $s$ for all gamma distributions. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/topic-modeling-poisson-170307081618-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A modified version of the manuscript Published on Feb 3, 2017. 1. Use a gamma prior for $r_k$. 2. Use the same shape parameter $s$ for all gamma distributions.
Topic modeling with Poisson factorization (2) from Tomonari Masada
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Poisson factorization /slideshow/poisson-factorization-71709461/71709461 poisson-factorization-170203043411
update equations derivation for Poisson factorization in topic modeling]]>

update equations derivation for Poisson factorization in topic modeling]]>
Fri, 03 Feb 2017 04:34:11 GMT /slideshow/poisson-factorization-71709461/71709461 tmasada@slideshare.net(tmasada) Poisson factorization tmasada update equations derivation for Poisson factorization in topic modeling <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/poisson-factorization-170203043411-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> update equations derivation for Poisson factorization in topic modeling
Poisson factorization from Tomonari Masada
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A Simple Stochastic Gradient Variational Bayes ?for the Correlated Topic Model /slideshow/a-simple-stochastic-gradient-variational-bayes-for-the-correlated-topic-model/69805991 masadaapweb2016-161204134820
poster presentation APWeb 2016 @ Suzhou, China]]>

poster presentation APWeb 2016 @ Suzhou, China]]>
Sun, 04 Dec 2016 13:48:20 GMT /slideshow/a-simple-stochastic-gradient-variational-bayes-for-the-correlated-topic-model/69805991 tmasada@slideshare.net(tmasada) A Simple Stochastic Gradient Variational Bayes ?for the Correlated Topic Model tmasada poster presentation APWeb 2016 @ Suzhou, China <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/masadaapweb2016-161204134820-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> poster presentation APWeb 2016 @ Suzhou, China
A Simple Stochastic Gradient Variational Bayes for the Correlated Topic Model from Tomonari Masada
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A Simple Stochastic Gradient Variational Bayes for Latent Dirichlet Allocation /slideshow/a-simple-stochastic-gradient-variational-bayes-for-latent-dirichlet-allocation-69805964/69805964 masadaiccsa2016-161204134627
ICCSA 2016 @ Beijing]]>

ICCSA 2016 @ Beijing]]>
Sun, 04 Dec 2016 13:46:26 GMT /slideshow/a-simple-stochastic-gradient-variational-bayes-for-latent-dirichlet-allocation-69805964/69805964 tmasada@slideshare.net(tmasada) A Simple Stochastic Gradient Variational Bayes for Latent Dirichlet Allocation tmasada ICCSA 2016 @ Beijing <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/masadaiccsa2016-161204134627-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ICCSA 2016 @ Beijing
A Simple Stochastic Gradient Variational Bayes for Latent Dirichlet Allocation from Tomonari Masada
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Word count in Husserliana Volumes 1 to 28 https://de.slideshare.net/slideshow/word-counts-in-husserliana-volumes-1-to-28/60312663 termfreq-160401024640
http://ophen.org/series-506 ]]>

http://ophen.org/series-506 ]]>
Fri, 01 Apr 2016 02:46:40 GMT https://de.slideshare.net/slideshow/word-counts-in-husserliana-volumes-1-to-28/60312663 tmasada@slideshare.net(tmasada) Word count in Husserliana Volumes 1 to 28 tmasada http://ophen.org/series-506 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/termfreq-160401024640-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> http://ophen.org/series-506
from Tomonari Masada
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A Simple Stochastic Gradient Variational Bayes for Latent Dirichlet Allocation /tmasada/a-simple-stochastic-gradient-variational-bayes-for-latent-dirichlet-allocation myiccsa2016-160327130427
To appear in ICCSA 2016. The manuscript for a review.]]>

To appear in ICCSA 2016. The manuscript for a review.]]>
Sun, 27 Mar 2016 13:04:26 GMT /tmasada/a-simple-stochastic-gradient-variational-bayes-for-latent-dirichlet-allocation tmasada@slideshare.net(tmasada) A Simple Stochastic Gradient Variational Bayes for Latent Dirichlet Allocation tmasada To appear in ICCSA 2016. The manuscript for a review. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/myiccsa2016-160327130427-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> To appear in ICCSA 2016. The manuscript for a review.
A Simple Stochastic Gradient Variational Bayes for Latent Dirichlet Allocation from Tomonari Masada
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FDSE2015 /slideshow/fdse2015/59636448 masadafdse2015-160316144912
http://dx.doi.org/10.1007/978-3-319-26135-5_10]]>

http://dx.doi.org/10.1007/978-3-319-26135-5_10]]>
Wed, 16 Mar 2016 14:49:11 GMT /slideshow/fdse2015/59636448 tmasada@slideshare.net(tmasada) FDSE2015 tmasada http://dx.doi.org/10.1007/978-3-319-26135-5_10 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/masadafdse2015-160316144912-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> http://dx.doi.org/10.1007/978-3-319-26135-5_10
FDSE2015 from Tomonari Masada
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https://cdn.slidesharecdn.com/profile-photo-tmasada-48x48.jpg?cb=1663849554 MY RESEARCH GOAL: Extracting latent DIVERSITIES from data with MATHEMATICAL MODELING. Specialties: data mining, Bayesian modeling, information retrieval, Web mining tomonari-masada.github.io/ https://cdn.slidesharecdn.com/ss_thumbnails/learninglatentspaceenergybasedpriormodel-220715143120-a9a338ef-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/learning-latent-space-energy-based-prior-model-252194923/252194923 Learning Latent Space ... https://cdn.slidesharecdn.com/ss_thumbnails/memo20200913diffusionmodels-200913132644-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/denoising-diffusion-probabilistic-models/238467087 Denoising Diffusion Pr... https://cdn.slidesharecdn.com/ss_thumbnails/kdweb2019paper1-190621104646-thumbnail.jpg?width=320&height=320&fit=bounds tmasada/contextdependent-tokenwise-variational-autoencoder-for-topic-modeling Context-dependent Toke...