Calysto Scheme

Calysto Scheme is a Scheme-based programming environment translated into Python, designed primarily for educational purposes but finding broader utility due to its simplicity and integration with the Jupyter Notebook ecosystem. Research focuses on leveraging its Python foundation to enhance its capabilities, particularly in areas like machine learning and incorporating features such as nondeterministic operators and Python interoperability. Its ease of use and accessibility make it a valuable tool for teaching programming concepts and potentially for other applications requiring a flexible and easily integrated scripting language.

Papers

November 21, 2022

Novel transfer learning schemes based on Siamese networks and synthetic data
Dominik Stallmann, Philip Kenneweg, Barbara Hammer
Transfer Learning Synthetic Data Style Transfer Siamese Network Single Cell Calysto Scheme

October 3, 2022

Accelerate Reinforcement Learning with PID Controllers in the Pendulum Simulations
Liping Bai
Reinforcement Learning Calysto Scheme Proportional Integral Derivative

July 12, 2022

A review of schemes for fingerprint image quality computation
Fernando Alonso-Fernandez, Julian Fierrez-Aguilar, Javier Ortega-Garcia
Narrative Review Fingerprint Recognition Calysto Scheme Fingerprint Image Fingerprint Image Quality

May 19, 2022

Why only Micro-F1? Class Weighting of Measures for Relation Classification
David Harbecke, Yuxuan Chen, Leonhard Hennig, Christoph Alt
Imbalanced Datasets New Measure Calysto Scheme Relation Classification Class Weight Weighting Scheme

May 9, 2022

An Effective Scheme for Maize Disease Recognition based on Deep Networks
Saeedeh Osouli, Behrouz Bolourian Haghighi, Ehsan Sadrossadat
Deep Neural Network Transfer Learning Deep Network Convolution Layer Plant Disease Calysto Scheme Maize Plant

May 6, 2022

All Grains, One Scheme (AGOS): Learning Multi-grain Instance Representation for Aerial Scene Classification
Qi Bi, Beichen Zhou, Kun Qin, Qinghao Ye, Gui-Song Xia
Calysto Scheme Aerial Scene Classification Multi Grained

April 10, 2022

Real order total variation with applications to the loss functions in learning schemes
Pan Liu, Xin Yang Lu, Kunlun He
Financial Application Loss Function Total Variation Fractional Derivative Calysto Scheme

January 12, 2022

Fast and accurate waveform modeling of long-haul multi-channel optical fiber transmission using a hybrid model-data driven scheme
Hang Yang, Zekun Niu, Haochen Zhao, Shilin Xiao, Weisheng Hu, Lilin Yi
Optical Network Calysto Scheme Fourier Analysis Waveform Model Light Propagation

December 16, 2021

A new locally linear embedding scheme in light of Hessian eigenmap
Liren Lin, Chih-Wei Chen
Projection Bias Light Work Calysto Scheme Manifold Dimension Explicit Weight Hessian Eigenvectors