【未明の一冊】.森賀新／木田悠歩／須山敦志・著.『Pythonではじめるベイズ機械学習入門』. 確率的プログラミング言語がすぐに使える‼️🤩.▶️PyMC3、Pyro、NumPyro、TFP、GPyTorchをカバー。.▶️回帰モデルの基本から潜在変数モデル・深層学習モデルまでを幅広く解説。

AI Best: GPyTorch! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode .

"The GPyTorch package has been employed to demonstrate the power of multivariate Gaussian Process regression to model volatile financial time series."

My drug discovery route has also become ML route. Its maths and madness, also python. Was able to run the k-fold cross validation code on GP with GPyTorch and 20:80 split. Not sure if good result. Will cross check with benchamrking paper

ぐはぁ😩.ぐはーーー😩. ガウス過程潜在変数モデル・・・僕の脳みそでは消化できない😵.ってゆーか、GPyTorchの実装方法も理解できてないから尚更😮‍💨.PyMC3で解説してほしかった。。。. まぁ、しゃーない。.いつか、理解できる日が来ると信じて先に進もう。. #Python #ベイズ統計 #機械学習

絶望的に意味分からん・・・・😂😂.GPyTorchによるガウス過程回帰の誘導点を使用した変分推論法. ガウス過程のパート、期待してたのに・・・.どうして、PyMCで実装してくれなかったのか😩.データ量が多い時は、ベイズではなく機械学習モデルを使うから、計算量なんて気にしなくても良いのに。。。

Exciting news! Say goodbye to standard Gaussian Processes and welcome Conformal Gaussian Processes. Harris Papadopoulos has released GPyConform! 🚀. GPyConform is a Python package that builds on GPyTorch, enabling Gaussian Process Regression with both symmetric and asymmetric

"On an NVIDIA Tesla V100 GPU, FastKron provides up to 40.7x speedup over GPyTorch and 6.40x over COGENT. On a system with 16 NVIDIA Tesla V100 GPUs, FastKron performs 7.85x better than CTF and 5.33x better than Distal."

AI Best: Gaussian Process using GPyTorch. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode.

Using GPyTorch — A Researcher’s Experience @linuxfoundation #DataScience #OpenSource

Tuning and struggling for whole month and seems find way to address my issue. Thanks gpytorch, it's absolutely useful tool.

A look at how GPyTorch and other open source projects can be beneficial for computational and statistical research. #DataScience #DataAnalytics #OpenSource @linuxfoundation.

【好評既刊】.森賀新／木田悠歩／須山敦志・著.『Pythonではじめるベイズ機械学習入門』. 🌟確率的プログラミング言語がすぐに使える‼️🌟.▶️Pythonでのコーディングを前提に、PyMC3、Pyro、NumPyro、TFP、GPyTorchをカバー。

GPyTorch’s documentation

@edward_milsom This type of batched CG is well supported in GPyTorch. See equations 3 & 7 of

ここ数日で、Transformer、Tabnet、GPy、GPyTorchとか、その他諸々のアルゴリズムの実装コードを書きまくったので、だいぶコードのストックが増やせた.他にもCatBoostのマニアックな機能を試してみたり、、、. まあ、どれも動かせただけで使いこなせてはいないが.

Learn from Astra Zhao's experience of exploring and using GPyTorch, and how open source projects can be beneficial for computational and statistical research. spon by @linuxfoundation #OpenSource #DataScience #DataAnalytics.

@miniapeur @edward_milsom @andrewgwils For independent outputs, it seems like there's no magic in GPyTorch's implementation: Everything seems to work as long as the kernel has shape (D,N,N) and the RHS is (D,N,1) or something like that.

Using GPyTorch — A Researcher’s Experience (Guassian Process Modeling).