23 papers · ranked by Valyu relevance
W. Jeffrey Johnston, Stephanie E. Palmer, David J. Freedman
Neuronal activity in the brain is variable, yet both perception and behavior are generally reliable. How does the brain achieve this? Here, we show that the conjunctive coding of multiple stimulus features, commonly known as nonlinear mixed selectivity, may be used by the brain to support reliable information…
W. Jeffrey Johnston, Stephanie E. Palmer, David J. Freedman, Stefano Fusi
'Stefano Fusi'] Neuronal activity in the brain is variable, yet both perception and behavior are generally reliable. How does the brain achieve this? Here, we show that the conjunctive coding of multiple stimulus features, commonly known as nonlinear mixed selectivity, may be used by the brain to support reliable…
Analay Perez, Rae Sakakibara, Srikar Baireddy, Michael D Fetters + 2 more
'Timothy C Guetterman' 'Amaryllis Mavragani'] Title: Abstract Background The patient-physician dyad involves both verbal and nonverbal communication. Traditional methods use quantitative or qualitative coding when analyzing dyadic data of nonverbal communication. Quantitative coding methods can capture the frequency of…
Mirko Klukas, Marcus Lewis, Ila Fiete, Daniel Bush
We shed light on the potential of entorhinal grid cells to efficiently encode variables of dimension greater than two, while remaining faithful to empirical data on their low-dimensional structure. Our model constructs representations of high-dimensional inputs through a combination of low-dimensional random…
Julijana Gjorgjieva, Markus Meister, Haim Sompolinsky
In many sensory systems the neural signal is coded by multiple parallel pathways, suggesting an evolutionary fitness benefit of general nature. A common pathway splitting is that into ON and OFF cells, responding to stimulus increments and decrements, respectively. According to efficient coding theory, sensory neurons…
Manik Sheokand, Parth Sawant
Large Language Models (LLMs) have achieved remarkable success in code generation tasks, powering various applications like code completion, debugging, and programming assistance. However, existing benchmarks such as HumanEval, MBPP, and BigCodeBench primarily evaluate LLMs on English-only prompts, overlooking the…
Felix Leditzky, Nilanjana Datta
The simplest example of a quantum information source with memory is a mixed source which emits signals entirely from one of two memoryless quantum sources with given a priori probabilities. Considering a mixed source consisting of a general one-parameter family of memoryless sources, we derive the second order…
Zeming Dong, Qiang Hu, Yuejun Guo, Maxime Cordy + 3 more
'Yves Le Traon' 'Jianjun Zhao'] Abstract—Inspired by the great success of Deep Neural Networks (DNNs) in natural language processing (NLP), DNNs have been increasingly applied in source code analysis and attracted significant attention from the software engineering community. Due to its data-driven nature, a DNN model…
Ian Holmes
We describe a strategy for constructing codes for DNA-based information storage by serial composition of weighted finite-state transducers. The resulting state machines can integrate correction of substitution errors; synchronization by interleaving watermark and periodic marker signals; conversion from binary to…
Dhiraj Amin, Sharvari Govilkar, Sagar Kulkarni, Yash Shashikant Lalit + 3 more
'Yash Shashikant Lalit' 'Arshi Ajaz Khwaja' 'Daries Xavier' 'Sahil Girijashankar Gupta'] Abstract— Code-mixing, the blending of linguistic elements from distinct languages to form meaningful sentences, is common in multilingual settings, yielding hybrid languages like Hinglish and Minglish. Marathi, India's third most…
Dmitry A. Dmitriev, Roman A. Rakitov, Gary Stormo
Direct Sanger sequencing of a diploid template containing a heterozygous insertion or deletion results in a difficult-to-interpret mixed trace formed by two allelic traces superimposed onto each other. Existing computational methods for deconvolution of such traces require knowledge of a reference sequence or the…
Anubhav Gupta, A. Bhogal, Kripabandhu Ghosh
of Code-Mixed Sentences Authors: ['Anubhav Gupta' 'A. Bhogal' 'Kripabandhu Ghosh'] Code-mixing, the practice of alternating between two or more languages in an utterance, is a common phenomenon in multilingual communities. Due to the colloquial nature of code-mixing, there is no singular correct way to translate an…
Prashant Kodali, Anmol Goel, Likhith Asapu, Vamshi Krishna Bonagiri + 4 more
Code-Mixed Sentences Authors: ['Prashant Kodali' 'Anmol Goel' 'Likhith Asapu' 'Vamshi Krishna Bonagiri' 'Anirudh Govil' 'Monojit Choudhury' 'Manish Shrivastava' 'Ponnurangam Kumaraguru'] Current computational approaches for analysing or generating code-mixed sentences do not explicitly model "naturalness" or…
Ismo Strandén, Ole F Christensen
Background Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker effects. In…
Thomas Lynn, Julio Ottino, Richard Lueptow, Paul Umbanhowar
Cut-and-shuffle mixing is an instructive candidate system with which to assess the potential of machine learning (ML) as an approach to solve difficult mixing problems. We focus on a specific subset of cut-and-shuffle systems, the one-dimensional interval exchange transform. This class of mixing operations is well…
David H Wyllie, Esther Robinson, Tim Peto, Derrick W Crook + 6 more
Detecting laboratory cross-contamination and mixed tuberculosis infection are important goals of clinical Mycobacteriology laboratories. To develop a method detecting mixtures of different M. tuberculosis lineages in laboratories performing Mycobacterial next generation sequencing (NGS). Public Health England National…
Authors not listed
Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
Zhangchen Xu, Yang Liu, Yueqin Yin, Mingyuan Zhou + 1 more
We introduce KODCODE, a synthetic dataset that addresses the persistent challenge of acquiring high-quality, verifiable training data across diverse difficulties and domains for training Large Language Models for coding. Existing code-focused resources typically fail to ensure either the breadth of coverage (e.g.…
Mingyu Gan, Qingyun Liu, Chongguang Yang, Qian Gao + 2 more
'Igor Mokrousov'] Mixed infection by multiple Mycobacterium tuberculosis (MTB) strains is associated with poor treatment outcome of tuberculosis (TB). Traditional genotyping methods have been used to detect mixed infections of MTB, however, their sensitivity and resolution are limited. Deep whole-genome sequencing…
VP Brintha, Manikandan Narayanan
Multi-drug resistant or hetero-resistant Tuberculosis (TB) hinders the successful treatment of TB. Hetero-resistant TB occurs when multiple strains of the TB-causing bacterium with varying degrees of drug susceptibility are present in an individual. Existing studies predicting the proportion and identity of strains in…
Authors not listed
Gibbs’ paradox—the apparent discontinuity in mixing entropy for gases of varying similarity and the seeming reversibility of mixing-separation cycles—has resisted fully satisfactory resolution for 150 years. We present a solution based on categorical state theory, which posits that physical con f igurations are…
Zhenlong Dai, Chang Yao, WenKang Han, Ying Yuan + 2 more
Implicit Style Representation Learning Authors: ['Zhenlong Dai' 'Chang Yao' 'WenKang Han' 'Ying Yuan' 'Zhipeng Gao' 'Jingyuan Chen'] Large Language Models (LLMs) have demonstrated great potential for assisting developers in their daily development. However, most research focuses on generating correct code, how to use…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…