The 30-Day .NET Challenge – Day 25: Use Exception Filters

Learn to enhance your C# code’s readability by avoiding multiple catch blocks. Discover a better approach using Exception Filters on Day 25 of our 30-Day .NET Challenge. Introduction The article demonstrates the use of exception filters to improve the readability, maintainability and performance of the application. Learning Objectives The problem with traditional exception handling Efficient … Read more

Blockchain is Shaping the Future of Athletics

The infusion of digital assets into sports is not just a fleeting trend but a profound disruption. It is reshaping everything from fan engagement to financial transactions, sponsorship deals, and even the very essence of sports memorabilia. Let’s dive into how cryptocurrency is revolutionizing the sports realm. Fan Engagement and Experiences Cryptocurrencies are redefining the … Read more

Blockchain SaaS And The Future Of Business: Exclusive Interview With OnchainLabs CEO Florian Ehrbar

Gartner, a leading research and advisory firm, recently predicted a significant rise in the value-add of enterprise blockchain by 2030, fueled by the increasing need for scalable business solutions, secure transactions, and the inherent benefits of decentralization offered by blockchain technology. Although B2B blockchain SaaS solutions are still in the early stages of adoption, they … Read more

Efficient Neural Network Approaches for Conditional Optimal Transport: Discussion and Reference

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Zheyu Oliver Wang, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA and olivrw@mit.edu; (2) Ricardo Baptista, Computing + Mathematical Sciences, California Institute of Technology, Pasadena, CA and rsb@caltech.edu; (3) Youssef Marzouk, Department of Aeronautics and Astronautics, Massachusetts Institute of … Read more

Efficient Neural Network Approaches for Conditional Optimal Transport: Numerical Experiments

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Zheyu Oliver Wang, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA and olivrw@mit.edu; (2) Ricardo Baptista, Computing + Mathematical Sciences, California Institute of Technology, Pasadena, CA and rsb@caltech.edu; (3) Youssef Marzouk, Department of Aeronautics and Astronautics, Massachusetts Institute of … Read more

Efficient Neural Network Approaches: Implementation and Experimental Setup

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Zheyu Oliver Wang, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA and olivrw@mit.edu; (2) Ricardo Baptista, Computing + Mathematical Sciences, California Institute of Technology, Pasadena, CA and rsb@caltech.edu; (3) Youssef Marzouk, Department of Aeronautics and Astronautics, Massachusetts Institute of … Read more

Efficient Neural Network Approaches for Conditional Optimal Transport:Conditional OT flow (COT-Flow)

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Zheyu Oliver Wang, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA and olivrw@mit.edu; (2) Ricardo Baptista, Computing + Mathematical Sciences, California Institute of Technology, Pasadena, CA and rsb@caltech.edu; (3) Youssef Marzouk, Department of Aeronautics and Astronautics, Massachusetts Institute of … Read more

Efficient Neural Network Approaches: Partially Convex Potential Maps (PCP-Map) for Conditional OT

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Zheyu Oliver Wang, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA and olivrw@mit.edu; (2) Ricardo Baptista, Computing + Mathematical Sciences, California Institute of Technology, Pasadena, CA and rsb@caltech.edu; (3) Youssef Marzouk, Department of Aeronautics and Astronautics, Massachusetts Institute of … Read more

Efficient Neural Network Approaches for Conditional Optimal Transport: Background and Related Work

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Zheyu Oliver Wang, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA and olivrw@mit.edu; (2) Ricardo Baptista, Computing + Mathematical Sciences, California Institute of Technology, Pasadena, CA and rsb@caltech.edu; (3) Youssef Marzouk, Department of Aeronautics and Astronautics, Massachusetts Institute of … Read more

Efficient Neural Network Approaches for Conditional Optimal Transport: Abstract & Introduction

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Zheyu Oliver Wang, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA and olivrw@mit.edu; (2) Ricardo Baptista, Computing + Mathematical Sciences, California Institute of Technology, Pasadena, CA and rsb@caltech.edu; (3) Youssef Marzouk, Department of Aeronautics and Astronautics, Massachusetts Institute of … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Experimental Datasets and Model

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Algorithms

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments: Conclusion, Limitations, and References

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Derivations

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Methods

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Experiments

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Background

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Related Work

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Abstract & Introduction

:::info This paper is available on arxiv under CC 4.0 license. Authors: (1) Sam Bowyer, Equal contribution, Department of Mathematics and sam.bowyer@bristol.ac.uk; (2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and thomas.heap@bristol.ac.uk; (3) Laurence Aitchison, Department of Computer Science University of Bristol and laurence.aitchison@bristol.ac.uk. ::: Table of Links Abstract & Introduction … Read more

The Illusion of Being Stuck

You think that being stuck is a permanent state, and this is the pattern you go through every time: You encounter a new challenge. Your brain resists it. It hasn’t been trained to handle discomfort effectively. You revert to what’s comfortable and familiar. You shut yourself off from potential growth and enlightenment. You feel stuck, … Read more

Homelab: Why You Need It and Where To Start

Are you a computer enthusiast? Want to learn new things like Virtualization, Docker, Kubernetes, touch HW and networking; or sharpen your skills? Or maybe run your own home infrastructure like NAS, Media server for family members, Ubiquity network controller, run a heart of your smart home – HomeAssistant? The answer is – Homelab Ok, what’s … Read more

The 30-Day .NET Challenge – Day 24: How to Avoid Exceptions in Flow Control

Exceptions are designed to handle unexpected situations rather than controlling the application flow. Using exceptions during input validation can affect your application’s readability and performance. Learning Objectives The inefficient use of exceptions A better approach using TryParse Prerequisites for Developers Basic understanding of C# programming language. 30 Day .Net Challenge Getting Started The inefficient use … Read more

Enhancing Interoperability in LMIC Healthcare Information Systems

:::info Authors: (1) Prabath Jayatissa, University of Colombo (2) Roshan Hewapathirane, University of Colombo ::: Table of Links Abstract & Introduction Methodology Results Conclusion & References 4. CONCLUSION Interoperability among health information systems is crucial for improving healthcare delivery in low and middle-income countries (LMICs) where access to quality healthcare is often limited. However, achieving … Read more