29 citations · 52 across the 24 of their papers we have counts for
27 papers
Multilevel Plaquette-Space Sampling for Lattice Gauge Theories with Local Constraint Solves
Ankur Singha, Jacob Finkenrath, Karl Jansen +2
Lattice gauge theories are an important class of physical models with high-dimensional structured distributions that underpin first-principles calculations in particle, nuclear, an…
Sector-Resolved Flow Sampling for Topologically Frozen Lattice Gauge Theories
Ankur Singha, Jacob Kauffmann, Karl Jansen +3
Topological fluctuations are essential to nonperturbative gauge theories but become increasingly difficult to sample toward the continuum limit, where Markov chains can freeze in s…
Probing Criticality Using GMM-Based Potentials
Shashank Sharma, Dipankar Chakrabarti, Vipul Arora
Spin models with a given symmetry are easier to sample than scalar theories with the same symmetry on a lattice, as the constrained nature of spin variables enables cheap heat-bath…
BEST-STD2.0: Balanced and Efficient Speech Tokenizer for Spoken Term Detection
Anup Singh, Vipul Arora, Kris Demuynck
Fast and accurate spoken content retrieval is vital for applications such as voice search. Query-by-Example Spoken Term Detection (STD) involves retrieving matching segments from a…
AudioNet: Supervised Deep Hashing for Retrieval of Similar Audio Events
Sagar Dutta, Vipul Arora
This work presents a supervised deep hashing method for retrieving similar audio events. The proposed method, named AudioNet, is a deep-learning-based system for efficient hashing…
CodecSep: Prompt-Driven Universal Sound Separation on Neural Audio Codec Latents
Adhiraj Banerjee, Vipul Arora
Text-guided sound separation enables flexible audio editing, assistive listening, and open-domain source extraction, but systems such as AudioSep remain too expensive for low-laten…
H-QuEST: Accelerating Query-by-Example Spoken Term Detection with Hierarchical Indexing
Akanksha Singh, Yi-Ping Phoebe Chen, Vipul Arora
Query-by-example spoken term detection (QbE-STD) searches for matching words or phrases in an audio dataset using a sample spoken query. When annotated data is limited or unavailab…
Uncertainty Quantification in Melody Estimation using Histogram Representation
Kavya Ranjan Saxena, Vipul Arora
Confidence estimation can improve the reliability of melody estimation by indicating which predictions are likely incorrect. The existing classification-based approach provides con…
BEST-STD: Bidirectional Mamba-Enhanced Speech Tokenization for Spoken Term Detection
Anup Singh, Kris Demuynck, Vipul Arora
Spoken term detection (STD) is often hindered by reliance on frame-level features and the computationally intensive DTW-based template matching, limiting its practicality. To addre…
Interactive singing melody extraction based on active adaptation
Kavya Ranjan Saxena, Vipul Arora
Extraction of predominant pitch from polyphonic audio is one of the fundamental tasks in the field of music information retrieval and computational musicology. To accomplish this t…
Improvement of Heatbath Algorithm in LFT using Generative models
Ali Faraz, Ankur Singha, Dipankar Chakrabarti +2
The Heatbath Algorithm is commonly used for sampling in local lattice field theories, but performing exact updates or sampling from the local density is challenging when dealing wi…
Sampling U(1) gauge theory using a re-trainable conditional flow-based model
Ankur Singha, Dipankar Chakrabarti, Vipul Arora
Sampling topological quantities in the Monte Carlo simulation of Lattice Gauge Theory becomes challenging as we approach the continuum limit of the theory. In this work, we introdu…
Near-Optimal Degree Testing for Bayes Nets
Vipul Arora, Arnab Bhattacharyya, Clément L. Canonne +1
This paper considers the problem of testing the maximum in-degree of the Bayes net underlying an unknown probability distribution over , given sample access to .…
Separating Key Agreement and Computational Differential Privacy
Vipul Arora, Eldon Chung, Zeyong Li +1
Two party differential privacy allows two parties who do not trust each other, to come together and perform a joint analysis on their data whilst maintaining individual-level priva…
Balanced Deep CCA for Bird Vocalization Detection
Sumit Kumar, B. Anshuman, Linus Ruettimann +2
Event detection improves when events are captured by two different modalities rather than just one. But to train detection systems on multiple modalities is challenging, in particu…
Simultaneously Learning Robust Audio Embeddings and balanced Hash codes for Query-by-Example
Anup Singh, Kris Demuynck, Vipul Arora
Audio fingerprinting systems must efficiently and robustly identify query snippets in an extensive database. To this end, state-of-the-art systems use deep learning to generate com…
Leveraging unsupervised data and domain adaptation for deep regression in low-cost sensor calibration
Swapnil Dey, Vipul Arora, Sachchida Nand Tripathi
Air quality monitoring is becoming an essential task with rising awareness about air quality. Low cost air quality sensors are easy to deploy but are not as reliable as the costly…
Deep domain adaptation for polyphonic melody extraction
Kavya Ranjan Saxena, Vipul Arora
Extraction of the predominant pitch from polyphonic audio is one of the fundamental tasks in the field of music information retrieval and computational musicology. To accomplish th…
Attention-Based Audio Embeddings for Query-by-Example
Anup Singh, Kris Demuynck, Vipul Arora
An ideal audio retrieval system efficiently and robustly recognizes a short query snippet from an extensive database. However, the performance of well-known audio fingerprinting sy…
Conditional Normalizing flow for Monte Carlo sampling in lattice scalar field theory
Ankur Singha, Dipankar Chakrabarti, Vipul Arora
The cost of Monte Carlo sampling of lattice configurations is very high in the critical region of lattice field theory due to the high correlation between the samples. This paper s…
Low Degree Testing over the Reals
Vipul Arora, Arnab Bhattacharyya, Noah Fleming +2
We study the problem of testing whether a function is a polynomial of degree at most in the \emph{distribution-free} testing model. Here, the d…
SyncNet: correlating objective for time delay estimation in audio signals
Akshay Raina, Vipul Arora
This study addresses the task of performing robust and reliable time-delay estimation in signals in noisy and reverberating environments. In contrast to the popular signal processi…
Generative learning for the problem of critical slowing down in lattice Gross Neveu model
Ankur Singha, Dipankar Chakrabarti, Vipul Arora
In lattice field theory, Monte Carlo simulation algorithms get highly affected by critical slowing down in the critical region, where autocorrelation time increases rapidly. Hence…
Few-shot calibration of low-cost air pollution (PM2.5) sensors using meta-learning
Kalpit Yadav, Vipul Arora, Sonu Kumar Jha +2
Low-cost particulate matter sensors are transforming air quality monitoring because they have lower costs and greater mobility as compared to reference monitors. Calibration of the…