activity
20132025
most citedA Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction

373 citations · 1.1k across the 25 of their papers we have counts for

collaborators

29 papers

q-bio.NC2025

Monkey Perceptogram: Reconstructing Visual Representation and Presumptive Neural Preference from Monkey Multi-electrode Arrays

Teng Fei, Srinivas Ravishankar, Hoko Nakada +5

Understanding how the primate brain transforms complex visual scenes into coherent perceptual experiences remains a central challenge in neuroscience. Here, we present a comprehens…

cs.CV2022

Multimodal Wildland Fire Smoke Detection

Siddhant Baldota, Shreyas Anantha Ramaprasad, Jaspreet Kaur Bhamra +9

Research has shown that climate change creates warmer temperatures and drier conditions, leading to longer wildfire seasons and increased wildfire risks in the United States. These…

cs.CV2021★ 82 cited

FIgLib & SmokeyNet: Dataset and Deep Learning Model for Real-Time Wildland Fire Smoke Detection

Anshuman Dewangan, Yash Pande, Hans-Werner Braun +5

The size and frequency of wildland fires in the western United States have dramatically increased in recent years. On high-fire-risk days, a small fire ignition can rapidly grow an…

eess.AS2020

Speech Recognition and Multi-Speaker Diarization of Long Conversations

Huanru Henry Mao, Shuyang Li, Julian McAuley +1

Speech recognition (ASR) and speaker diarization (SD) models have traditionally been trained separately to produce rich conversation transcripts with speaker labels. Recent advance…

cs.AI2020★ 3 cited

Generating Rationales in Visual Question Answering

Hammad A. Ayyubi, Md. Mehrab Tanjim, Julian J. McAuley +1

Despite recent advances in Visual QuestionAnswering (VQA), it remains a challenge todetermine how much success can be attributedto sound reasoning and comprehension ability.We seek…

cs.LG2020★ 149 cited

ReZero is All You Need: Fast Convergence at Large Depth

Thomas Bachlechner, Bodhisattwa Prasad Majumder, Huanru Henry Mao +2

Deep networks often suffer from vanishing or exploding gradients due to inefficient signal propagation, leading to long training times or convergence difficulties. Various architec…