11 citations · 14 across the 9 of their papers we have counts for
10 papers
Lower Bounds for the Algorithmic Complexity of Learned Indexes
Luis Alberto Croquevielle, Roman Sokolovskii, Thomas Heinis
Learned index structures aim to accelerate queries by training machine learning models to approximate the rank function associated with a database attribute. While effective in pra…
High-fidelity robotic PCR amplification
Vincent Beguin, Jean Grétillat, Kornelija Kaminskaitė +14
Polymerase chain reaction (PCR) underpins modern molecular biology, yet its deployment in emerging domains such as DNA data storage and distributed diagnostics remains constrained…
Balanced Online Class-Incremental Learning via Dual Classifiers
Shunjie Wen, Thomas Heinis, Dong-Wan Choi
Online class-incremental learning (OCIL) focuses on gradually learning new classes (called plasticity) from a stream of data in a single-pass, while concurrently preserving knowled…
A New Paradigm in Tuning Learned Indexes: A Reinforcement Learning Enhanced Approach
Taiyi Wang, Liang Liang, Guang Yang +2
Learned Index Structures (LIS) have significantly advanced data management by leveraging machine learning models to optimize data indexing. However, designing these structures ofte…
Motif Caller: Sequence Reconstruction for Motif-Based DNA Storage
Parv Agarwal, Nimesh Pinnamaneni, Thomas Heinis
DNA data storage is rapidly emerging as a promising solution for long-term data archiving, largely due to its exceptional durability. However, the synthesis of DNA strands remains…
An End-to-End Coding Scheme for DNA-Based Data Storage With Nanopore-Sequenced Reads
Lorenz Welter, Roman Sokolovskii, Thomas Heinis +3
We consider error-correcting coding for deoxyribonucleic acid (DNA)-based storage using nanopore sequencing. We model the DNA storage channel as a sampling noise channel where the…
Single Exposure Quantitative Phase Imaging with a Conventional Microscope using Diffusion Models
Gabriel della Maggiora, Luis Alberto Croquevielle, Harry Horsley +2
Phase imaging is gaining importance due to its applications in fields like biomedical imaging and material characterization. In biomedical applications, it can provide quantitative…
Coding Over Coupon Collector Channels for Combinatorial Motif-Based DNA Storage
Roman Sokolovskii, Parv Agarwal, Luis Alberto Croquevielle +2
Encoding information in combinations of pre-synthesised deoxyribonucleic acid (DNA) strands (referred to as motifs) is an interesting approach to DNA storage that could potentially…
Querying in Constant Expected Time with Learned Indexes
Luis Croquevielle, Guang Yang, Liang Liang +2
Learned indexes leverage machine learning models to accelerate query answering in databases, showing impressive practical performance. However, theoretical understanding of these m…
Conditional Variational Diffusion Models
Gabriel della Maggiora, Luis Alberto Croquevielle, Nikita Deshpande +3
Inverse problems aim to determine parameters from observations, a crucial task in engineering and science. Lately, generative models, especially diffusion models, have gained popul…