Talks
All the talks so far.
Exploring Long-term (Time-)Series Forecasting (LTSF) using Echo State Networks (ESNs) and comparisons with Single-Layer Perceptron (SLP), MLP, LSTM and especially Attention-based methods
Jyotirmaya ShivottamPublished: at 12:14 AMThis talk will explore Echo State Networks (ESNs) and their applications in Long-term (Time-)Series Forecasting (LTSF). We will compare ESNs with Single-Layer Perceptron (SLP), Multi-Layer Perceptron (MLP), Long Short-Term Memory (LSTM) networks, and especially attention-based methods for LTSF.
End-to-end Object Detection with Transformers
Rucha Bhalchandra JoshiPublished: at 02:00 PMThis talk presents DETR, a new method for object detection that streamlines the pipeline by removing the need for components like non-maximum suppression and anchor generation.
You Only Look Once - Unified, Real-Time Object Detection
Aritra MukhopadhayaPublished: at 02:00 PMThis talk discusses YOLO, a groundbreaking method for object detection. YOLO revolutionizes object detection with real-time processing, using a single network for bounding box and class probability predictions, excelling in speed and domain generalization.
DT-Solver - Automated Theorem Proving with Dynamic-Tree Sampling Guided by Proof-level Value Function
Rahul VishwakarmaPublished: at 02:00 PMThis talk discusses DT-Solver, a novel approach to automated theorem proving that uses dynamic-tree Monte-Carlo search and a proof-level value function for improved state exploration.
End-to-end Object Detection with Transformers
Rucha Bhalchandra JoshiPublished: at 02:00 PMThis talk presents DETR, a new method for object detection that streamlines the pipeline by removing the need for components like non-maximum suppression and anchor generation.
Handling position and visibility discontinuities for physically-based differentiable rendering
Annada Prasad BeheraPublished: at 02:00 PMIn this talk, we discuss handling position and visibility discontinuities for physically-based differentiable rendering.