4 citations · 6 across the 11 of their papers we have counts for
12 papers
Geo-vision: Native-Resolution Geometry and Sampled Topology for Vehicle-Part Damage Classification
Usef Faghihi, Amir Saki, Serge Jonathan Kogbeti-Wongo
Geo-vision classifies vehicle-part damage using a fixed representation combining appearance, multiscale geometry, orientation, and sampled digital topology. Connected components, h…
Common-Witness Certificates and Sharp Feature Bounds for Counterfactual Image Auditing
Usef Faghihi, Amir Saki
An image editor may satisfy every regional plausibility constraint separately even when no single latent explanation fits the complete output. We formalize this local-to-global fai…
Causal inference for group-contaminated structured outcomes: observable quotients, lossless reduction and exact randomization inference
Usef Faghihi, Amir Saki
Structured potential outcomes such as microscopy images may be recorded after an unknown, unit-specific transformation. If that transformation can depend on treatment, covariates o…
Topological Ignorability for Structural Causal Effects Beyond Means
Usef Faghihi
Many interventions alter the structure of an outcome distribution rather than its mean: they can split a population into disconnected regimes, create loops or holes, generate branc…
Global and Local Topology-Aware Attention with Persistent Homology and Euler Biases for Time-Series Forecasting
Usef Faghihi, Amir Saki
Scientific time series often encode predictive geometric structure, including connectivity, cycles, shell-like geometry, directional changes, and nonlinear neighborhoods, that stan…
Beyond Means: Topological Causal Effects under Persistent-Homology Ignorability
Amir Saki, Usef Faghihi
Average treatment effects (ATE) and conditional average treatment effects (CATE) are foundational causal estimands, but they target changes in expected outcomes and can miss treatm…
Causal Deep Q Network
Elouanes Khelifi, Amir Saki, Usef Faghihi
Deep Q Networks (DQN) have shown remarkable success in various reinforcement learning tasks. However, their reliance on associative learning often leads to the acquisition of spuri…
Integrating Fuzzy Logic with Causal Inference: Enhancing the Pearl and Neyman-Rubin Methodologies
Amir Saki, Usef Faghihi
In this paper, we generalize the Pearl and Neyman-Rubin methodologies in causal inference by introducing a generalized approach that incorporates fuzzy logic. Indeed, we introduce…
Probabilistic Easy Variational Causal Effect
Usef Faghihi, Amir Saki
Let and be random vectors, and . In this paper, on the one hand, for the case that and are continuous, by using the ideas from the total variation and the…
Probabilistic Variational Causal Approach in Observational Studies
Usef Faghihi, Amir Saki
In this paper, we introduce a new causal methodology that accounts for the rarity and frequency of events in observational studies based on their relevance to the underlying proble…
A Fundamental Probabilistic Fuzzy Logic Framework Suitable for Causal Reasoning
Amir Saki, Usef Faghihi
In this paper, we introduce a fundamental framework to create a bridge between Probability Theory and Fuzzy Logic. Indeed, our theory formulates a random experiment of selecting cr…
How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent
Usef Faghihi, Philippe Fournier-Viger, Roger Nkambou +2
In this paper we propose the CTS (Concious Tutoring System) technology, a biologically plausible cognitive agent based on human brain functions.This agent is capable of learning an…