6 citations · 10 across the 5 of their papers we have counts for
6 papers
LVMem: Image-Augmented Memory for Long-Horizon Question Answering
Victoria Khoruzhaya, Maksim Kalmykov, Tuong Do Minh +3
Reliable language-guided perception is essential for embodied agents, where questions about objects, events, and their locations must be answered from long observation histories. U…
CNN on `Top': In Search of Scalable & Lightweight Image-based Jet Taggers
Rajneil Baruah, Subhadeep Mondal, Sunando Kumar Patra +1
While Transformer-based and standard Graph Neural Networks (GNNs) have proven to be the best performers in classifying different types of jets, they require substantial computation…
Amortized Inference of Multi-Modal Posteriors using Likelihood-Weighted Normalizing Flows
Rajneil Baruah
We present a novel technique for amortized posterior estimation using Normalizing Flows trained with likelihood-weighted importance sampling. This approach allows for the efficient…
Normalizing Flow-Assisted Nested Sampling on Type-II Seesaw Model
Rajneil Baruah, Subhadeep Mondal, Sunando Kumar Patra +1
We propose a novel technique for sampling particle physics model parameter space. The main sampling method applied is Nested Sampling (NS), which is boosted by the application of m…
Probing sub-TeV Higgsinos aided by a ML-based top tagger in the context of Trilinear RPV SUSY
Rajneil Baruah, Arghya Choudhury, Kirtiman Ghosh +2
Probing higgsinos remains a challenge at the LHC owing to their small production cross-sections and the complexity of the decay modes of the nearly mass degenerate higgsino states.…
Probing intractable beyond-standard-model parameter spaces armed with Machine Learning
Rajneil Baruah, Subhadeep Mondal, Sunando Kumar Patra +1
This article attempts to summarize the effort by the particle physics community in addressing the tedious work of determining the parameter spaces of beyond-the-standard-model (BSM…