Latest posts tagged with #MachineLearningEngineering on Bluesky
On my way to #NeurIPS2025! Happy to chat about @iopp-mlresearch.bsky.social #MachineLearningScienceandTechnology, #MachineLearningHealth, #MachineLearningEarth, and #MachineLearningEngineering 🤖 Thursday through Sunday, or at our booth in the Exhibitor space (Booth T4). Come say hi! 😊 #EditorsLife
🌟Recently published in #MachineLearningEngineering: Real-time Detection of Insulator Defects Based on Improved Wavelet Scattering Convolutional Network.
Available to read and download today 👉https://ow.ly/qSSH50XtWzw
🆕🔖Check out this #openaccess article published in #MachineLearningEngineering 👉 Predicting electronic properties of π-conjugated organic polymers using machine learning for optoelectronic applications.
Download and cite today: https://ow.ly/35i550XtWue
Recently published article in #MachineLearningEngineering
"Exploring model #generalizability from a novel perspective"
👉Read, download and cite here: ow.ly/wq2z50X9ziZ
From Sunyang Wang, Baodi Yu and Fanyong Meng, Institute of Process Engineering, Chinese Academy of Sciences
Recently published #PerspectiveArticle in #MachineLearningEngineering
Discover work on building a systematic, scalable framework for Engineering AI
Read here: ow.ly/8PN250WHGNn
By Jay Lee, Hanqi Su, Dai-Yan Ji and Takanobu Minami
#AIFramework #AIinEngineering #AppliedMachineLearning
Recently published in #MachineLearningEngineering 🥳
Read the #openaccess article: 'Understanding interpretable patterns of Shapley behaviours in materials data'
👉 ow.ly/bmmN50WHE2X
From Tommy Liu and Amanda S Barnard, (Australian National University)
#DataAnalysis #ExplainableArtificialIntelligence
Discover #MachineLearningEngineering
Delivering accessible, cutting-edge #research, focused on the development and application of #MachineLearning across #engineering —including theoretical, methodological, and real-world innovations.
🗨️Hear from our Editor-in-Chief Jay Lee: ow.ly/yByW50WFXp6
If you’re into #MachineLearning and (any flavor of) #engineering, then #MachineLearningEngineering is the right journal for you *wink wink*
Always happy to chat about this journal, go have a look at the first issue 😊 🤖🦾
A graph showing my household’s monthly consumption of gas. The letters on the x axis indicate the months of the year (Dec through April), while the y axis (units not shown) is the monthly consumption. Light grey means estimated reading, while dark grey is the actual reading.
On the phone with the gas company for a bill that’s definitely too high: “We use sophisticated #AI models to estimate our customers’ monthly consumption”
Can I recommend reading our #MachineLearningEngineering (@iopp-mlresearch.bsky.social) to make those models better? #EditorsLife
Friendly reminder that the three new journals in the Machine Learning series (Machine Learning: Health, Machine Learning: Earth, and Machine Learning: Engineering) are now open for and accepting submissions
As we get ready for the weekend (#Friyay), your favorite friendly neighborhood editor wants to remind everyone that #MachineLearningHealth, #MachineLearningEarth, and #MachineLearningEngineering are open for submissions 😊 #MachineLearning #IOPPublishing
