42 citations · 57 across the 9 of their papers we have counts for
9 papers
Neuro-Symbolic Financial Reasoning via Deterministic Fact Ledgers and Adversarial Low-Latency Hallucination Detector
Pedram Agand
Standard Retrieval-Augmented Generation (RAG) architectures fail in high-stakes financial domains due to two fundamental limitations: the inherent arithmetic incompetence of Large…
Beyond Static Datasets: Robust Offline Policy Optimization via Vetted Synthetic Transitions
Pedram Agand, Mo Chen
Offline Reinforcement Learning (ORL) holds immense promise for safety-critical domains like industrial robotics, where real-time environmental interaction is often prohibitive. A p…
Sequential Modeling of Complex Marine Navigation: Case Study on a Passenger Vessel (Student Abstract)
Yimeng Fan, Pedram Agand, Mo Chen +3
The maritime industry's continuous commitment to sustainability has led to a dedicated exploration of methods to reduce vessel fuel consumption. This paper undertakes this challeng…
LeTFuser: Light-weight End-to-end Transformer-Based Sensor Fusion for Autonomous Driving with Multi-Task Learning
Pedram Agand, Mohammad Mahdavian, Manolis Savva +1
In end-to-end autonomous driving, the utilization of existing sensor fusion techniques and navigational control methods for imitation learning proves inadequate in challenging situ…
Deep Reinforcement Learning-based Intelligent Traffic Signal Controls with Optimized CO2 emissions
Pedram Agand, Alexey Iskrov, Mo Chen
Nowadays, transportation networks face the challenge of sub-optimal control policies that can have adverse effects on human health, the environment, and contribute to traffic conge…
Fuel Consumption Prediction for a Passenger Ferry using Machine Learning and In-service Data: A Comparative Study
Pedram Agand, Allison Kennedy, Trevor Harris +3
As the importance of eco-friendly transportation increases, providing an efficient approach for marine vessel operation is essential. Methods for status monitoring with considerati…
Adaptive Model Learning of Neural Networks with UUB Stability for Robot Dynamic Estimation
Pedram Agand, Mahdi Aliyari Shoorehdeli
Since batch algorithms suffer from lack of proficiency in confronting model mismatches and disturbances, this contribution proposes an adaptive scheme based on continuous Lyapunov…
DMODE: Differential Monocular Object Distance Estimation Module without Class Specific Information
Pedram Agand, Michael Chang, Mo Chen
Utilizing a single camera for measuring object distances is a cost-effective alternative to stereo-vision and LiDAR. Although monocular distance estimation has been explored in the…
Online Probabilistic Model Identification using Adaptive Recursive MCMC
Pedram Agand, Mo Chen, Hamid D. Taghirad
Although the Bayesian paradigm offers a formal framework for estimating the entire probability distribution over uncertain parameters, its online implementation can be challenging…