Mirascope’s Post

Excited to share our recent paper titled ‘A generalized Chebyshev operational method for Volterra integro-partial differential equations with weakly singular kernels‘. It introduces a Matrix Collocation Method for solving Volterra integro-partial differential equations with weakly singular kernels (VIPDEWSK). The approach utilizes Shifted Chebyshev Polynomials of the Fifth Kind (SCPFK) to construct pseudo-operational matrices, avoiding explicit integration for faster computations. Error bounds are analyzed in a Chebyshev-weighted space, offering insights into approximation accuracy. Big thanks to Professor Sadri and the other co-authors for their collaborative efforts. You can access the article right here: 2024DOI:https://lnkd.in/evHB66Qj https://lnkd.in/e98gmPwf

mirascope stores everything that goes into and comes out of a call to an LLM in the response the responses are also Pydantic `BaseModel` instances so dumping all of this information is super easy docs: https://lnkd.in/gRQr34Sw

In this paper, the authors propose a random subspace sampling method, RSS, by sampling missing items from the corresponding feature histogram distributions in random subspaces, which is effective and efficient at different levels of missing data. https://lnkd.in/gypE8rNr Jianxin Wu

Particle Cave Remastered - Dev Diary 1 https://lnkd.in/e9y255EJ New Project Announcement! I'm resmastering the Particle Cave demo to bring it up to date with the latest workflows

annotating and @pydantic BaseModel response model in mirascope with `FromCallArgs` will populate the field with the value from the call's arguments rather than have the LLM generate it this enables colocation of validation of generated fields against the call arguments. docs: https://lnkd.in/gXx7GRDa

Excited to share my latest project where I utilized logistic regression to distinguish between minerals and rocks based on various features. From data exploration to model training, it's been a fascinating journey unraveling the hidden patterns in geology. GitHub repo-- https://lnkd.in/gqVVepA4 #DataScience #LogisticRegression #Geology #machinelearning

https://lnkd.in/gziUnkmw (best with landscape view) This is the first edition of Geosense Magazine🥳 I hope this magazine will greatly introduce Geospatial field and expertise, greatly academics purposes and as a space for students who want to collaborate to publish their own map based on our issues subscribe our magazine by clicking follow and DM or email me for more info about our mission and contributor guideline

Big thank you to Jen Woronow for this excellent article she wrote on Project Athena for the Havok Journal! "We see the world around us through different gazes. Whether it is a strategic, birds-eye view or a close investigation at the ground level, multiple perspectives shape how we interpret information. No one vantage point reveals the entire picture. Maps can show where a journey has taken us and where we have yet to go, but can maps offer something in between?" Please check it out here: https://lnkd.in/ecpB7ggu

Pleased to have our paper titled “Quantifying Virtual Field Trip Efficiency” published online today. In the paper we present a quantitative assessment of time, cost, logistical efficiency, carbon emissions, and achievement of learning outcomes for a virtual field trip to Utah, comparing the data directly to its physical field trip counterpart. https://lnkd.in/e4SmfexT John Howell, Adrian Hartley, Simon Buckley, Magda Chmielewska, Nicole Naumann, Prof. Nick Schofield, Rachel Brackenridge

🌊 Exciting News from @JMSE_MDPI! 🚀 The latest #NewArticle, "RDCP: A Real Time Sea Fog Intensity and Visibility Estimation Algorithm," has been published. This innovative algorithm offers real-time, accurate estimation of sea fog intensity and visibility. 👉 Dive into the research: https://lnkd.in/dgcXCN9X #MarineScience #SeaFog #Research