papers

Publications (24)

cs.CV2022

Variable Bitrate Neural Fields

Towaki Takikawa, Alex Evans, Jonathan Tremblay +4

Neural approximations of scalar and vector fields, such as signed distance functions and radiance fields, have emerged as accurate, high-quality representations. State-of-the-art r…

cs.CV2023

BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects

Bowen Wen, Jonathan Tremblay, Valts Blukis +6

We present a near real-time method for 6-DoF tracking of an unknown object from a monocular RGBD video sequence, while simultaneously performing neural 3D reconstruction of the obj…

q-fin.MF2022

A primer on perpetuals

Guillermo Angeris, Tarun Chitra, Alex Evans +1

We consider a continuous-time financial market with no arbitrage and no transactions costs. In this setting, we introduce two types of perpetual contracts, one in which the payoff…

cs.CV2023

Compact Neural Graphics Primitives with Learned Hash Probing

Towaki Takikawa, Thomas Müller, Merlin Nimier-David +4

Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid…

math.OC2023

The Geometry of Constant Function Market Makers

Guillermo Angeris, Tarun Chitra, Theo Diamandis +2

Constant function market makers (CFMMs) are the most popular type of decentralized trading venue for cryptocurrency tokens. In this paper, we give a very general geometric framewor…

cs.CV2022

Instant Neural Graphics Primitives with a Multiresolution Hash Encoding

Thomas Müller, Alex Evans, Christoph Schied +1

Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate. We reduce this cost with a versatile new input encoding that perm…

cs.CV2023

Neuralangelo: High-Fidelity Neural Surface Reconstruction

Zhaoshuo Li, Thomas Müller, Alex Evans +4

Neural surface reconstruction has been shown to be powerful for recovering dense 3D surfaces via image-based neural rendering. However, current methods struggle to recover detailed…

q-fin.MF2021

Optimal Fees for Geometric Mean Market Makers

Alex Evans, Guillermo Angeris, Tarun Chitra

Constant Function Market Makers (CFMMs) are a family of automated market makers that enable censorship-resistant decentralized exchange on public blockchains. Arbitrage trades have…

q-fin.MF2020

Liquidity Provider Returns in Geometric Mean Markets

Alex Evans

Geometric mean market makers (G3Ms), such as Uniswap and Balancer, comprise a popular class of automated market makers (AMMs) defined by the following rule: the reserves of the AMM…

q-fin.TR2021

Replicating Monotonic Payoffs Without Oracles

Guillermo Angeris, Alex Evans, Tarun Chitra

In this paper, we show that any monotonic payoff can be replicated using only liquidity provider shares in constant function market makers (CFMMs), without the need for additional…

cs.GR2024

Real-Time Neural Appearance Models

Tizian Zeltner, Fabrice Rousselle, Andrea Weidlich +7

We present a complete system for real-time rendering of scenes with complex appearance previously reserved for offline use. This is achieved with a combination of algorithmic and s…

cs.CV2023

Extracting Triangular 3D Models, Materials, and Lighting From Images

Jacob Munkberg, Jon Hasselgren, Tianchang Shen +5

We present an efficient method for joint optimization of topology, materials and lighting from multi-view image observations. Unlike recent multi-view reconstruction approaches, wh…

math.OC2022

Dynamic Pricing for Non-fungible Resources: Designing Multidimensional Blockchain Fee Markets

Theo Diamandis, Alex Evans, Tarun Chitra +1

Public blockchains implement a fee mechanism to allocate scarce computational resources across competing transactions. Most existing fee market designs utilize a joint, fungible un…

cs.CV2023

Parallel Inversion of Neural Radiance Fields for Robust Pose Estimation

Yunzhi Lin, Thomas Müller, Jonathan Tremblay +5

We present a parallelized optimization method based on fast Neural Radiance Fields (NeRF) for estimating 6-DoF pose of a camera with respect to an object or scene. Given a single o…

math.OC2022

Optimal Routing for Constant Function Market Makers

Guillermo Angeris, Tarun Chitra, Alex Evans +1

We consider the problem of optimally executing an order involving multiple crypto-assets, sometimes called tokens, on a network of multiple constant function market makers (CFMMs).…

math.OC2021

Constant Function Market Makers: Multi-Asset Trades via Convex Optimization

Guillermo Angeris, Akshay Agrawal, Alex Evans +2

The rise of Ethereum and other blockchains that support smart contracts has led to the creation of decentralized exchanges (DEXs), such as Uniswap, Balancer, Curve, mStable, and Su…

q-fin.MF2021

Replicating Market Makers

Guillermo Angeris, Alex Evans, Tarun Chitra

We present a method for constructing Constant Function Market Makers (CFMMs) whose portfolio value functions match a desired payoff. More specifically, we show that the space of co…

cs.CV2022

RTMV: A Ray-Traced Multi-View Synthetic Dataset for Novel View Synthesis

Jonathan Tremblay, Moustafa Meshry, Alex Evans +9

We present a large-scale synthetic dataset for novel view synthesis consisting of ~300k images rendered from nearly 2000 complex scenes using high-quality ray tracing at high resol…

q-fin.GN2020

Why Stake When You Can Borrow?

Tarun Chitra, Alex Evans

As smart contract platforms autonomously manage billions of dollars of capital, quantifying the portfolio risk that investors engender in these systems is increasingly important. R…

cs.RO2024

Enhancing Human-Robot Collaborative Assembly in Manufacturing Systems Using Large Language Models

Jonghan Lim, Sujani Patel, Alex Evans +3

The development of human-robot collaboration has the ability to improve manufacturing system performance by leveraging the unique strengths of both humans and robots. On the shop f…

cs.GT2023

Concave Pro-rata Games

Nicholas A. G Johnson, Theo Diamandis, Alex Evans +2

In this paper, we introduce a family of games called concave pro-rata games. In such a game, players place their assets into a pool, and the pool pays out some concave function of…

cs.CR2021

A Note on Privacy in Constant Function Market Makers

Guillermo Angeris, Alex Evans, Tarun Chitra

Constant function market makers (CFMMs) such as Uniswap, Balancer, Curve, and mStable, among many others, make up some of the largest decentralized exchanges on Ethereum and other…

cs.CL2024

The Mysterious Case of Neuron 1512: Injectable Realignment Architectures Reveal Internal Characteristics of Meta's Llama 2 Model

Brenden Smith, Dallin Baker, Clayton Chase +6

Large Language Models (LLMs) have an unrivaled and invaluable ability to "align" their output to a diverse range of human preferences, by mirroring them in the text they generate.…

q-fin.TR2020

When does the tail wag the dog? Curvature and market making

Guillermo Angeris, Alex Evans, Tarun Chitra

Liquidity and trading activity on constant function market makers (CFMMs) such as Uniswap, Curve, and Balancer has grown significantly in the second half of 2020. Much of the growt…